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2009
Conference article
Restricted
Search the web x.0: mining and recommending web-mediated processes
Tolomei G.
Nowadays, people have been increasingly interested in exploiting Web Search Engines (WSEs) not only for having access to simple Web pages, but mainly for accomplishing even complex activities, namely Web-mediated processes (or taskflows). Thus, users' information needs will become more complex, and Web search and recommender systems should change accordingly for dealing with this shift. We claim that such taskflows and their composing tasks are implicitly present in users' minds when they interact with a WSE to access the Web. Our first research challenge is thus to evaluate this belief by analyzing a very large, long-term log of queries submitted to a WSE, and associating meaningful semantic labels with the extracted tasks (i.e., clusters of related queries) and taskflows. This large knowledge base constitutes a good starting point for building a model of users' behaviors. The second research challenge is to devise a novel recommender system that goes beyond the simple query suggestion of modern WSEs. Our system has to exploit the knowledge base of Web-mediated processes and the learned model of users' behaviors, to generate complex insights and task-based suggestions to incoming users while they interact with a WSE.Source: Third ACM Conference on Recommender systems, pp. 417–420, New York City - USA, 22-25/10 2009
DOI: 10.1145/1639714.1639803
Metrics:
Tolomei G.
Nowadays, people have been increasingly interested in exploiting Web Search Engines (WSEs) not only for having access to simple Web pages, but mainly for accomplishing even complex activities, namely Web-mediated processes (or taskflows). Thus, users' information needs will become more complex, and Web search and recommender systems should change accordingly for dealing with this shift. We claim that such taskflows and their composing tasks are implicitly present in users' minds when they interact with a WSE to access the Web. Our first research challenge is thus to evaluate this belief by analyzing a very large, long-term log of queries submitted to a WSE, and associating meaningful semantic labels with the extracted tasks (i.e., clusters of related queries) and taskflows. This large knowledge base constitutes a good starting point for building a model of users' behaviors. The second research challenge is to devise a novel recommender system that goes beyond the simple query suggestion of modern WSEs. Our system has to exploit the knowledge base of Web-mediated processes and the learned model of users' behaviors, to generate complex insights and task-based suggestions to incoming users while they interact with a WSE.Source: Third ACM Conference on Recommender systems, pp. 417–420, New York City - USA, 22-25/10 2009
DOI: 10.1145/1639714.1639803
Metrics:
See at:
dl.acm.org 
| doi.org | CNR ExploRA
2002
Report
Open Access
I principi e le tecnologie utili alla realizzazione di una interfaccia web accessibile alle persone disabili
Miori V., Tolomei G.
Il documento, dopo aver esplorato i principi generali di accessibilità e usabilità nel mondo web, offre una descrizione delle tecnologie utilizzate per la progettazione e realizzazione di un prototipo di interfaccia web, per un sistema informativo distribuito basato sulla rete, rispondente ai criteri di progettazione universale. La rassegna di tali fondamenti teorici, fa parte del lavoro svolto per lo studio rivolto alla realizzazione di un'interfaccia Web accessibile alle persone disabili, nell'ambito di un progetto congiunto ISTI-CNR e Ministero dell'Ambiente, denominato INFEA. Si rimanda al documento ISTI B4-23, per le ulteriori informazioni e approfondimenti riguardo le soluzioni tecnologiche specificatamente adottate e la descrizione delle modalità di realizzazione del prototipoSource: ISTI Technical reports, 2002
Miori V., Tolomei G.
Il documento, dopo aver esplorato i principi generali di accessibilità e usabilità nel mondo web, offre una descrizione delle tecnologie utilizzate per la progettazione e realizzazione di un prototipo di interfaccia web, per un sistema informativo distribuito basato sulla rete, rispondente ai criteri di progettazione universale. La rassegna di tali fondamenti teorici, fa parte del lavoro svolto per lo studio rivolto alla realizzazione di un'interfaccia Web accessibile alle persone disabili, nell'ambito di un progetto congiunto ISTI-CNR e Ministero dell'Ambiente, denominato INFEA. Si rimanda al documento ISTI B4-23, per le ulteriori informazioni e approfondimenti riguardo le soluzioni tecnologiche specificatamente adottate e la descrizione delle modalità di realizzazione del prototipoSource: ISTI Technical reports, 2002
See at:
ISTI Repository 
| CNR ExploRA
2002
Report
Open Access
Il disegno e la realizzazione di un prototipo di interfaccia web accessibile
Miori V., Tolomei G.
Il documento tratta della realizzazione di un'interfaccia accessibile agli utenti disabili per il sistema informativo INFEA. INFEA costituisce un significativo esempio di WIS (Web-based Information System) dedicato alla Pubblica Amministrazione, che coinviolge le iniziative rivolte allo Sviluppo Sostenibile del Ministero dell'Ambiente.Source: ISTI Technical reports, 2002
Miori V., Tolomei G.
Il documento tratta della realizzazione di un'interfaccia accessibile agli utenti disabili per il sistema informativo INFEA. INFEA costituisce un significativo esempio di WIS (Web-based Information System) dedicato alla Pubblica Amministrazione, che coinviolge le iniziative rivolte allo Sviluppo Sostenibile del Ministero dell'Ambiente.Source: ISTI Technical reports, 2002
See at:
ISTI Repository | CNR ExploRA
2012
Conference article
Open Access
Automatic analysis of multimodal requirements: a research preview.
Bruni E., Ferrari A., Seyff N., Tolomei G.
[Context and motivation] Traditionally, requirements are documented using natural language text. However, there exist several ap- proaches that promote the use of rich media requirements descriptions. Apart from text-based descriptions these multimodal requirements can be enriched by images, audio, or even video. [Question/Problem] The transcription and automated analysis of multimodal information is an important open question, which has not been sufficiently addressed by the Requirement Engineering (RE) community so far. Therefore, in this research preview paper we sketch how we plan to tackle research chal- lenges related to the field of multimodal requirements analysis. We are in particular focusing on the automation of the analysis process. [Prin- cipal idea/results] In our recent research we have started to gather and manually analyze multimodal requirements. Furthermore, we have worked on concepts which initially allow the analysis of multimodal in- formation. The purpose of the planned research is to combine and extend our recent work and to come up with an approach supporting the au- tomatic analysis of multimodal requirements. [Contribution] In this paper we give a preview on the planned work. We present our research goal, discuss research challenges and depict an early conceptual solution.Source: Requirements Engineering: Foundation for Software Quality. 18th International Working Conference, pp. 218–224, Essen, Germany, 19-22 marzo 2012
DOI: 10.1007/978-3-642-28714-5_19
Metrics:
Bruni E., Ferrari A., Seyff N., Tolomei G.
[Context and motivation] Traditionally, requirements are documented using natural language text. However, there exist several ap- proaches that promote the use of rich media requirements descriptions. Apart from text-based descriptions these multimodal requirements can be enriched by images, audio, or even video. [Question/Problem] The transcription and automated analysis of multimodal information is an important open question, which has not been sufficiently addressed by the Requirement Engineering (RE) community so far. Therefore, in this research preview paper we sketch how we plan to tackle research chal- lenges related to the field of multimodal requirements analysis. We are in particular focusing on the automation of the analysis process. [Prin- cipal idea/results] In our recent research we have started to gather and manually analyze multimodal requirements. Furthermore, we have worked on concepts which initially allow the analysis of multimodal in- formation. The purpose of the planned research is to combine and extend our recent work and to come up with an approach supporting the au- tomatic analysis of multimodal requirements. [Contribution] In this paper we give a preview on the planned work. We present our research goal, discuss research challenges and depict an early conceptual solution.Source: Requirements Engineering: Foundation for Software Quality. 18th International Working Conference, pp. 218–224, Essen, Germany, 19-22 marzo 2012
DOI: 10.1007/978-3-642-28714-5_19
Metrics:
See at:
Zurich Open Repository and Archive | www.zora.uzh.ch | doi.org | link.springer.com | CNR ExploRA
2014
Conference article
Restricted
Quite a mess in my cookie jar!: Leveraging machine learning to protect web authentication
Calzavara S., Tolomei G., Bugliesi M., Orlando S.
Browser-based defenses have recently been advocated as an effective mechanism to protect web applications against the threats of session hijacking, fixation, and related attacks. In existing approaches, all such defenses ultimately rely on client-side heuristics to automatically detect cookies containing session information, to then protect them against theft or otherwise unintended use. While clearly crucial to the effectiveness of the resulting defense mechanisms, these heuristics have not, as yet, undergone any rigorous assessment of their adequacy. In this paper, we conduct the first such formal assessment, based on a gold set of cookies we collect from 70 popular websites of the Alexa ranking. To obtain the gold set, we devise a semi-automatic procedure that draws on a novel notion of authentication token, which we introduce to capture multiple web authentication schemes. We test existing browser-based defenses in the literature against our gold set, unveiling several pitfalls both in the heuristics adopted and in the methods used to assess them. We then propose a new detection method based on supervised learning, where our gold set is used to train a binary classifier, and report on experimental evidence that our method outperforms existing proposals. Interestingly, the resulting classification, together with our hands-on experience in the construction of the gold set, provides new insight on how web authentication is implemented in practice. Copyright is held by the International World Wide Web Conference Committee (IW3C2).Source: www'14 - 23rd international conference on World Wide Web, pp. 189–199, Seul, Corea, 7-11 April 2014
DOI: 10.1145/2566486.2568047
Metrics:
Calzavara S., Tolomei G., Bugliesi M., Orlando S.
Browser-based defenses have recently been advocated as an effective mechanism to protect web applications against the threats of session hijacking, fixation, and related attacks. In existing approaches, all such defenses ultimately rely on client-side heuristics to automatically detect cookies containing session information, to then protect them against theft or otherwise unintended use. While clearly crucial to the effectiveness of the resulting defense mechanisms, these heuristics have not, as yet, undergone any rigorous assessment of their adequacy. In this paper, we conduct the first such formal assessment, based on a gold set of cookies we collect from 70 popular websites of the Alexa ranking. To obtain the gold set, we devise a semi-automatic procedure that draws on a novel notion of authentication token, which we introduce to capture multiple web authentication schemes. We test existing browser-based defenses in the literature against our gold set, unveiling several pitfalls both in the heuristics adopted and in the methods used to assess them. We then propose a new detection method based on supervised learning, where our gold set is used to train a binary classifier, and report on experimental evidence that our method outperforms existing proposals. Interestingly, the resulting classification, together with our hands-on experience in the construction of the gold set, provides new insight on how web authentication is implemented in practice. Copyright is held by the International World Wide Web Conference Committee (IW3C2).Source: www'14 - 23rd international conference on World Wide Web, pp. 189–199, Seul, Corea, 7-11 April 2014
DOI: 10.1145/2566486.2568047
Metrics:
See at:
dl.acm.org | doi.org | CNR ExploRA
2008
Journal article
Open Access
SPRANKER: a discovery tool to rank service providers using quality of experience
Nardini F. M., Silvestri F., Laforenza D., Tolomei G.
The HPC-Lab at ISTI-CNR is investigating the topic of service discovery with the aim of supporting service-oriented architectures (SOAs) on Grid computing infrastructures. We present a brief overview of SPRanker (Service Provider Ranker), a discovery tool that, unlike the usual service discovery components, retrieves provider information rather than service descriptions. At its core SPRanker exploits a score formula based on information retrieval that takes into account judgments expressed collaboratively by past service users.Source: ERCIM news 74 (2008): 23–24.
Nardini F. M., Silvestri F., Laforenza D., Tolomei G.
The HPC-Lab at ISTI-CNR is investigating the topic of service discovery with the aim of supporting service-oriented architectures (SOAs) on Grid computing infrastructures. We present a brief overview of SPRanker (Service Provider Ranker), a discovery tool that, unlike the usual service discovery components, retrieves provider information rather than service descriptions. At its core SPRanker exploits a score formula based on information retrieval that takes into account judgments expressed collaboratively by past service users.Source: ERCIM news 74 (2008): 23–24.
See at:
ercim-news.ercim.eu | CNR ExploRA
2005
Conference article
Restricted
An innovative, open-standards solution for Konnex interoperability with other domotic middlewares
Miori V., Tarrini L., Manca M., Tolomei G.
Two technical aspects need to be developed to reach the goal of interoperability: an open, standardized, and interoperable framework based on Web Services paradigm to provide seamless interoperability of services and applications, called DomoNet (Domotics Network); a standardized XML grammar to be used on the DomoNet infrastructure, DomoML (Domotics Markup Language). Following this approach, specifications for an architecture, that permits the integration of all the possible devices in a home environment, have been outlined. According to Konnex philosophy, the interaction model among the devices is similar to a network of distributed applications; however, the communication between the nodes in this network takes part through the use of Web Services standards and DomoML, instead of using the specific protocols of a particular domotic middleware. Just to exemplify, a prototype has been developed, in accordance with the proposed architectural specifications, to show the correctness of our solution through the integration of UPnP and Konnex lighting devices. To connect the Konnex middleware to DomoNet we had to develop a software interface that permits, on one side, the interaction with Konnex devices through the use of FALCON libraries and on the other side the communication with DomoNet Web Services through the use of DomoML.Source: Konnex Scientific Conference 2005, Pisa, September 15-16, 2005
Miori V., Tarrini L., Manca M., Tolomei G.
Two technical aspects need to be developed to reach the goal of interoperability: an open, standardized, and interoperable framework based on Web Services paradigm to provide seamless interoperability of services and applications, called DomoNet (Domotics Network); a standardized XML grammar to be used on the DomoNet infrastructure, DomoML (Domotics Markup Language). Following this approach, specifications for an architecture, that permits the integration of all the possible devices in a home environment, have been outlined. According to Konnex philosophy, the interaction model among the devices is similar to a network of distributed applications; however, the communication between the nodes in this network takes part through the use of Web Services standards and DomoML, instead of using the specific protocols of a particular domotic middleware. Just to exemplify, a prototype has been developed, in accordance with the proposed architectural specifications, to show the correctness of our solution through the integration of UPnP and Konnex lighting devices. To connect the Konnex middleware to DomoNet we had to develop a software interface that permits, on one side, the interaction with Konnex devices through the use of FALCON libraries and on the other side the communication with DomoNet Web Services through the use of DomoML.Source: Konnex Scientific Conference 2005, Pisa, September 15-16, 2005
See at:
www.konnex.org | CNR ExploRA
2006
Conference article
Restricted
DomoNet: a framework and a prototype for interoperability of domotics middlewares based on XML and WebServices
Miori V., Tarrini L., Manca M., Tolomei G.
This paper proposes a novel architecture based on the services oriented architecture (SOA) paradigm to enable the interoperability among domotic middlewares through a "universal" XML-based home automation language.Source: ICCE - International Conference on Consumer Electronics, pp. 117–118, Las Vegas, 7-11 January 2006
DOI: 10.1109/icce.2006.1598338
Metrics:
Miori V., Tarrini L., Manca M., Tolomei G.
This paper proposes a novel architecture based on the services oriented architecture (SOA) paradigm to enable the interoperability among domotic middlewares through a "universal" XML-based home automation language.Source: ICCE - International Conference on Consumer Electronics, pp. 117–118, Las Vegas, 7-11 January 2006
DOI: 10.1109/icce.2006.1598338
Metrics:
See at:
doi.org | ieeexplore.ieee.org | CNR ExploRA
2010
Conference article
Open Access
Towards a task-based search and recommender systems
Tolomei G., Orlando S., Silvestri F.
Nowadays, people have been increasingly interested in exploiting Web Search Engines (WSEs) not only for having access to simple Web pages, but mainly for carrying out even complex activities, namely Web-mediated processes (or taskflows). Therefore, users' information needs will become more complex, and (Web) search and recommender systems should change accordingly for dealing with this shift. We claim that such taskflows and their composing tasks are implicitly present in users' minds when they interact, thus, with a WSE to access the Web. Our first research challenge is thus to evaluate this belief by analyzing a very large, longterm log of queries submitted to a WSE, and associating meaningful semantic labels with the extracted tasks (i.e., clusters of task-related queries) and taskflows. This large knowledge base constitutes a good starting point for building a model of users' behaviors. The second research challenge is to devise a novel recommender system that goes beyond the simple query suggestion of modern WSEs. Our system has to exploit the knowledge base of Web-mediated processes and the learned model of users' behaviors, to generate complex insights and task-based suggestions to incoming users while they interact with a WSE.Source: IEEE 26th International Conference on Data Engineering, PhD Workshop, pp. 333–336, Long Beach, CA (USA), 1-6 Marzo 2010
DOI: 10.1109/icdew.2010.5452726
Metrics:
Tolomei G., Orlando S., Silvestri F.
Nowadays, people have been increasingly interested in exploiting Web Search Engines (WSEs) not only for having access to simple Web pages, but mainly for carrying out even complex activities, namely Web-mediated processes (or taskflows). Therefore, users' information needs will become more complex, and (Web) search and recommender systems should change accordingly for dealing with this shift. We claim that such taskflows and their composing tasks are implicitly present in users' minds when they interact, thus, with a WSE to access the Web. Our first research challenge is thus to evaluate this belief by analyzing a very large, longterm log of queries submitted to a WSE, and associating meaningful semantic labels with the extracted tasks (i.e., clusters of task-related queries) and taskflows. This large knowledge base constitutes a good starting point for building a model of users' behaviors. The second research challenge is to devise a novel recommender system that goes beyond the simple query suggestion of modern WSEs. Our system has to exploit the knowledge base of Web-mediated processes and the learned model of users' behaviors, to generate complex insights and task-based suggestions to incoming users while they interact with a WSE.Source: IEEE 26th International Conference on Data Engineering, PhD Workshop, pp. 333–336, Long Beach, CA (USA), 1-6 Marzo 2010
DOI: 10.1109/icdew.2010.5452726
Metrics:
See at:
ieeexplore.ieee.org | doi.org | CNR ExploRA
2011
Conference article
Open Access
Identifying task-based sessions in search engine query logs
Lucchese C., Orlando S., Perego R., Silvestri F., Tolomei G.
The research challenge addressed in this paper is to devise effective techniques for identifying task-based sessions, i.e. sets of possibly non contiguous queries issued by the user of a Web Search Engine for carrying out a given task. In order to evaluate and compare different approaches, we built, by means of a manual labeling process, a ground-truth where the queries of a given query log have been grouped in tasks. Our analysis of this ground-truth shows that users tend to perform more than one task at the same time, since about 75% of the submitted queries involve a multi-tasking activity. We formally define the Task-based Session Discovery Problem (TSDP) as the problem of best approximating the manually annotated tasks, and we propose several variants of well known clustering algorithms, as well as a novel efficient heuristic algorithm, specifically tuned for solving the TSDP. These algorithms also exploit the collaborative knowledge collected by Wiktionary and Wikipedia for detecting query pairs that are not similar from a lexical content point of view, but actually semantically related. The proposed algorithms have been evaluated on the above ground-truth, and are shown to perform better than state-of-the-art approaches, because they effectively take into account the multi-tasking behavior of users.Source: Fourth ACM International Conference on Web Search and Data Mining, pp. 277–286, Hong Kong, China, 10-12 Febbraio 2011
DOI: 10.1145/1935826.1935875
Project(s): S-CUBE
Metrics:
Lucchese C., Orlando S., Perego R., Silvestri F., Tolomei G.
The research challenge addressed in this paper is to devise effective techniques for identifying task-based sessions, i.e. sets of possibly non contiguous queries issued by the user of a Web Search Engine for carrying out a given task. In order to evaluate and compare different approaches, we built, by means of a manual labeling process, a ground-truth where the queries of a given query log have been grouped in tasks. Our analysis of this ground-truth shows that users tend to perform more than one task at the same time, since about 75% of the submitted queries involve a multi-tasking activity. We formally define the Task-based Session Discovery Problem (TSDP) as the problem of best approximating the manually annotated tasks, and we propose several variants of well known clustering algorithms, as well as a novel efficient heuristic algorithm, specifically tuned for solving the TSDP. These algorithms also exploit the collaborative knowledge collected by Wiktionary and Wikipedia for detecting query pairs that are not similar from a lexical content point of view, but actually semantically related. The proposed algorithms have been evaluated on the above ground-truth, and are shown to perform better than state-of-the-art approaches, because they effectively take into account the multi-tasking behavior of users.Source: Fourth ACM International Conference on Web Search and Data Mining, pp. 277–286, Hong Kong, China, 10-12 Febbraio 2011
DOI: 10.1145/1935826.1935875
Project(s): S-CUBE
Metrics:
See at:
www.dsi.unive.it | ACM Digital Library | doi.org | portal.acm.org | CNR ExploRA
2011
Conference article
Restricted
Improving Europeana search experience using query logs
Ceccarelli D., Gordea S., Lucchese C., Nardini F. M., Tolomei G.
Europeana is a long-term project funded by the European Commission with the goal of making Europe's cultural and scientific heritage accessible to the public. Since 2008, about 1500 institutions have contributed to Europeana, enabling people to explore the digital re- sources of Europe's museums, libraries and archives. The huge amount of collected multi-lingual multi-media data is made available today through the Europeana portal, a search engine allowing users to explore such con- tent through textual queries. One of the most important techniques for enhancing users search experience in large information spaces, is the exploitation of the knowledge contained in query logs. In this paper we present a characterization of the Europeana query log, showing statistics on common behavioral patterns of the Europeana users. Our analysis highlights some significative differences between the Europeana query log and the historical data collected by general purpose Web Search Engine logs. In particular, we find out that both query and search session distributions show different behaviors. Finally, we use this information for designing a query recommendation technique having the goal of enhancing the functionality of the Europeana portal.Source: Research and Advanced Technology for Digital Libraries. International Conference on Theory and Practice of Digital Libraries, pp. 384–395, Berlin, Germany, 26-27-28 SETTEMBRE 2011
DOI: 10.1007/978-3-642-24469-8_39
Project(s): ASSETS
Metrics:
Ceccarelli D., Gordea S., Lucchese C., Nardini F. M., Tolomei G.
Europeana is a long-term project funded by the European Commission with the goal of making Europe's cultural and scientific heritage accessible to the public. Since 2008, about 1500 institutions have contributed to Europeana, enabling people to explore the digital re- sources of Europe's museums, libraries and archives. The huge amount of collected multi-lingual multi-media data is made available today through the Europeana portal, a search engine allowing users to explore such con- tent through textual queries. One of the most important techniques for enhancing users search experience in large information spaces, is the exploitation of the knowledge contained in query logs. In this paper we present a characterization of the Europeana query log, showing statistics on common behavioral patterns of the Europeana users. Our analysis highlights some significative differences between the Europeana query log and the historical data collected by general purpose Web Search Engine logs. In particular, we find out that both query and search session distributions show different behaviors. Finally, we use this information for designing a query recommendation technique having the goal of enhancing the functionality of the Europeana portal.Source: Research and Advanced Technology for Digital Libraries. International Conference on Theory and Practice of Digital Libraries, pp. 384–395, Berlin, Germany, 26-27-28 SETTEMBRE 2011
DOI: 10.1007/978-3-642-24469-8_39
Project(s): ASSETS
Metrics:
See at:
doi.org | gateway.webofknowledge.com | www.springerlink.com | CNR ExploRA
2011
Report
Open Access
S-CUBE - Knowledge extraction from service usage
Silvestri F., Nardini F. M., Tolomei G.
Data is everywhere. Computer systems keep track of activities of users in the form of log files. Ranging from system logs on Web servers to logs collected by large-scale service based applications, this type of data represents a goldmine of knowledge that, once extracted, can help the stakeholders of the whole system to understand better if, and how, the application can be improved. To this aim, data mining consist of a set of techniques aiming at extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. With recent tremendous technical advances in processing power, storage capacity, and inter-connectivity of computer technology, data mining is seen as an increasingly important tool by modern business to transform unprecedented quantities of digital data into business intelligence giving an informational advantage. Service-centric systems are said to be flexible and dynamic. To support this flexibility, event processing mechanisms can be used to record which events occur within the system. This includes both basic "service events" (e.g., service is created) and complex events regarding QoS (e.g., average response time of service X has changed) and invocations (e.g., service X has been invoked), supporting complex event processing. Users can subscribe to various events of interest, and get notified either via email or Web service notifications (e.g., WS-Eventing). Such notifications may trigger adaptive behavior (e.g., rebinding to other services). Service Oriented Architectures (SOAs) are thus complex infrastructures consisting of thousands or millions of service interacting together in order to achieve complex operations (tasks). Service invocation logs are file tracing the interactions between services. As in other contexts, data mining techniques can be thus applied in order to derive useful knowledge. Such knowledge can be spent in order to enhance both effectiveness and efficiency of the overall infrastructure. The same approach within other fields like, for example, the Web domain is proven to be effective. The knowledge extracted by means of data mining techniques from query logs (files containing the interactions of the users with the search engine) is the first way a search engine improve its performances in terms of effectiveness and efficiency. In this deliverable we thus investigate how useful knowledge can be extracted from service logs and possible ways of applications within the SOA context. In order to do that as one of the case studies we will use logs from search engines activities to extract knowledge regarding users activity.Source: Project report, S-CUBE, Deliverable #PO-JRA-2.3.7, 2011
Project(s): S-CUBE
Silvestri F., Nardini F. M., Tolomei G.
Data is everywhere. Computer systems keep track of activities of users in the form of log files. Ranging from system logs on Web servers to logs collected by large-scale service based applications, this type of data represents a goldmine of knowledge that, once extracted, can help the stakeholders of the whole system to understand better if, and how, the application can be improved. To this aim, data mining consist of a set of techniques aiming at extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. With recent tremendous technical advances in processing power, storage capacity, and inter-connectivity of computer technology, data mining is seen as an increasingly important tool by modern business to transform unprecedented quantities of digital data into business intelligence giving an informational advantage. Service-centric systems are said to be flexible and dynamic. To support this flexibility, event processing mechanisms can be used to record which events occur within the system. This includes both basic "service events" (e.g., service is created) and complex events regarding QoS (e.g., average response time of service X has changed) and invocations (e.g., service X has been invoked), supporting complex event processing. Users can subscribe to various events of interest, and get notified either via email or Web service notifications (e.g., WS-Eventing). Such notifications may trigger adaptive behavior (e.g., rebinding to other services). Service Oriented Architectures (SOAs) are thus complex infrastructures consisting of thousands or millions of service interacting together in order to achieve complex operations (tasks). Service invocation logs are file tracing the interactions between services. As in other contexts, data mining techniques can be thus applied in order to derive useful knowledge. Such knowledge can be spent in order to enhance both effectiveness and efficiency of the overall infrastructure. The same approach within other fields like, for example, the Web domain is proven to be effective. The knowledge extracted by means of data mining techniques from query logs (files containing the interactions of the users with the search engine) is the first way a search engine improve its performances in terms of effectiveness and efficiency. In this deliverable we thus investigate how useful knowledge can be extracted from service logs and possible ways of applications within the SOA context. In order to do that as one of the case studies we will use logs from search engines activities to extract knowledge regarding users activity.Source: Project report, S-CUBE, Deliverable #PO-JRA-2.3.7, 2011
Project(s): S-CUBE
See at:
ISTI Repository | CNR ExploRA
2011
Report
Open Access
Mining lifecycle event logs for enhancing service-based applications
Nardini F. M., Tolomei G., Silvestri F., Leitner P., Dustdar S.
Service-Oriented Architectures (SOAs), and traditional enterprise systems in general, record a variety of events (e.g., messages being sent and received between service components) to proper log files, i.e., event logs. These files constitute a huge and valuable source of knowledge that may be extracted through data mining techniques. To this end, process mining is increasingly gaining interest across the SOA community. The goal of process mining is to build models without emph{a priori} knowledge, i.e., to discover structured process models derived from specific emph{patterns} that are present in actual traces of service executions recorded in event logs. However, in this work we focus on detecting frequent sequential patterns, thus considering process mining as a specific instance of the more general sequential pattern mining problem. Furthermore, we apply two sequential pattern mining algorithms to a real event log provided by the Vienna Runtime Environment for Service-oriented Computing, i.e., vresco. The obtained results show that we are able to find services that are frequently invoked together within the same sequence. Such knowledge could be useful at design-time, when service-based application developers could be provided with service recommendation tools that are able to predict and thus to suggest next services that should be included in the current service composition.Source: ISTI Technical reports, 2011
Project(s): S-CUBE
Nardini F. M., Tolomei G., Silvestri F., Leitner P., Dustdar S.
Service-Oriented Architectures (SOAs), and traditional enterprise systems in general, record a variety of events (e.g., messages being sent and received between service components) to proper log files, i.e., event logs. These files constitute a huge and valuable source of knowledge that may be extracted through data mining techniques. To this end, process mining is increasingly gaining interest across the SOA community. The goal of process mining is to build models without emph{a priori} knowledge, i.e., to discover structured process models derived from specific emph{patterns} that are present in actual traces of service executions recorded in event logs. However, in this work we focus on detecting frequent sequential patterns, thus considering process mining as a specific instance of the more general sequential pattern mining problem. Furthermore, we apply two sequential pattern mining algorithms to a real event log provided by the Vienna Runtime Environment for Service-oriented Computing, i.e., vresco. The obtained results show that we are able to find services that are frequently invoked together within the same sequence. Such knowledge could be useful at design-time, when service-based application developers could be provided with service recommendation tools that are able to predict and thus to suggest next services that should be included in the current service composition.Source: ISTI Technical reports, 2011
Project(s): S-CUBE
See at:
ISTI Repository | CNR ExploRA
2012
Contribution to book
Restricted
Mining lifecycle event logs for enhancing service-based applications
Dustdar S., Leitner P., Nardini F. M., Silvestri F., Tolomei G.
Service-Oriented Architectures (SOAs), and traditional enterprise systems in general, record a variety of events (e.g., messages being sent and received between service components) to proper log files, i.e., event logs. These files constitute a huge and valuable source of knowledge that may be extracted through data mining techniques. To this end, process mining is increasingly gaining interest across the SOA community. The goal of process mining is to build models without a priori knowledge, i.e., to discover structured process models derived from specific patterns that are present in actual traces of service executions recorded in event logs. However, in this work, the authors focus on detecting frequent sequential patterns, thus considering process mining as a specific instance of the more general sequential pattern mining problem. Furthermore, they apply two sequential pattern mining algorithms to a real event log provided by the Vienna Runtime Environment for Service-oriented Computing, i.e., VRESCo. The obtained results show that the authors are able to find services that are frequently invoked together within the same sequence. Such knowledge could be useful at design-time, when service-based application developers could be provided with service recommendation tools that are able to predict and thus to suggest next services that should be included in the current service composition.Source: Adaptive Web Services for Modular and Reusable Software Development: Tactics and Solutions, edited by Guadalupe Ortiz, Javier Cubo, pp. 196–206. Hershey: Information Science Reference, 2012
DOI: 10.4018/978-1-4666-2089-6.ch007
DOI: 10.4018/978-1-4666-2455-9.ch033
Project(s): S-CUBE
Metrics:
Dustdar S., Leitner P., Nardini F. M., Silvestri F., Tolomei G.
Service-Oriented Architectures (SOAs), and traditional enterprise systems in general, record a variety of events (e.g., messages being sent and received between service components) to proper log files, i.e., event logs. These files constitute a huge and valuable source of knowledge that may be extracted through data mining techniques. To this end, process mining is increasingly gaining interest across the SOA community. The goal of process mining is to build models without a priori knowledge, i.e., to discover structured process models derived from specific patterns that are present in actual traces of service executions recorded in event logs. However, in this work, the authors focus on detecting frequent sequential patterns, thus considering process mining as a specific instance of the more general sequential pattern mining problem. Furthermore, they apply two sequential pattern mining algorithms to a real event log provided by the Vienna Runtime Environment for Service-oriented Computing, i.e., VRESCo. The obtained results show that the authors are able to find services that are frequently invoked together within the same sequence. Such knowledge could be useful at design-time, when service-based application developers could be provided with service recommendation tools that are able to predict and thus to suggest next services that should be included in the current service composition.Source: Adaptive Web Services for Modular and Reusable Software Development: Tactics and Solutions, edited by Guadalupe Ortiz, Javier Cubo, pp. 196–206. Hershey: Information Science Reference, 2012
DOI: 10.4018/978-1-4666-2089-6.ch007
DOI: 10.4018/978-1-4666-2455-9.ch033
Project(s): S-CUBE
Metrics:
See at:
doi.org | doi.org | www.igi-global.com | CNR ExploRA
2013
Conference article
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Using clustering to improve the structure of natural language requirements documents
Ferrari A., Gnesi S., Tolomei G.
[Context and motivation] System requirements are nor- mally provided in the form of natural language documents. Such documents need to be properly structured, in order to ease the overall uptake of the requirements by the readers of the document. A structure that allows a proper understanding of a requirements document shall satisfy two main quality attributes: (i) requirements relatedness: each requirement is conceptually connected with the requirements in the same section; (ii) sections independence: each section is conceptually separated from the others. [Question/Problem] Automatically identifying the parts of the document that lack requirements relatedness and sections independence may help improve the document structure. [Principal idea/results] To this end, we define a novel clustering algorithm named Sliding Head-Tail Component (S-HTC). The algorithm groups together similar require- ments that are contiguous in the requirements document. We claim that such algorithm allows discovering the structure of the document in the way it is perceived by the reader. If the structure originally provided by the document does not match the structure discovered by the algorithm, hints are given to identify the parts of the document that lack requirements relatedness and sections independence. [Contribution] We evaluate the effectiveness of the algorithm with a pilot test on a requirements standard of the railway domain (583 requirements).Source: REFSQ 2013 - Requirements Engineering: Foundation for Software Quality. 19th International Working Conference, pp. 34–49, Essen, Germany, 08-11 Aprile 2013
DOI: 10.1007/978-3-642-37422-7_3
Metrics:
Ferrari A., Gnesi S., Tolomei G.
[Context and motivation] System requirements are nor- mally provided in the form of natural language documents. Such documents need to be properly structured, in order to ease the overall uptake of the requirements by the readers of the document. A structure that allows a proper understanding of a requirements document shall satisfy two main quality attributes: (i) requirements relatedness: each requirement is conceptually connected with the requirements in the same section; (ii) sections independence: each section is conceptually separated from the others. [Question/Problem] Automatically identifying the parts of the document that lack requirements relatedness and sections independence may help improve the document structure. [Principal idea/results] To this end, we define a novel clustering algorithm named Sliding Head-Tail Component (S-HTC). The algorithm groups together similar require- ments that are contiguous in the requirements document. We claim that such algorithm allows discovering the structure of the document in the way it is perceived by the reader. If the structure originally provided by the document does not match the structure discovered by the algorithm, hints are given to identify the parts of the document that lack requirements relatedness and sections independence. [Contribution] We evaluate the effectiveness of the algorithm with a pilot test on a requirements standard of the railway domain (583 requirements).Source: REFSQ 2013 - Requirements Engineering: Foundation for Software Quality. 19th International Working Conference, pp. 34–49, Essen, Germany, 08-11 Aprile 2013
DOI: 10.1007/978-3-642-37422-7_3
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2010
Conference article
Unknown
Detecting task-based query sessions using collaborative knowledge
Lucchese C., Orlando S., Perego R., Silvestri F., Tolomei G.
Our research challenge is to provide a mechanism for splitting into user task-based sessions a long-term log of queries submitted to a Web Search Engine (WSE). The hypothesis is that some query sessions entail the concept of user task. We present an approach that relies on a centroid-based and a density-based clustering algorithm, which consider queries inter-arrival times and use a novel distance function that takes care of query lexical content and exploits the collaborative knowledge collected by Wiktionary and Wikipedia.Source: 2010 International Workshop on Intelligent Web Interaction, Toronto, Canada, 31 Agosto 2010
Lucchese C., Orlando S., Perego R., Silvestri F., Tolomei G.
Our research challenge is to provide a mechanism for splitting into user task-based sessions a long-term log of queries submitted to a Web Search Engine (WSE). The hypothesis is that some query sessions entail the concept of user task. We present an approach that relies on a centroid-based and a density-based clustering algorithm, which consider queries inter-arrival times and use a novel distance function that takes care of query lexical content and exploits the collaborative knowledge collected by Wiktionary and Wikipedia.Source: 2010 International Workshop on Intelligent Web Interaction, Toronto, Canada, 31 Agosto 2010
See at: CNR ExploRA
2011
Journal article
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Discovering Europeana Users' Search Behavior
Ceccarelli D., Gordea S., Lucchese C., Nardini F. M., Perego R. Tolomei G.
Europeana is a strategic project funded by the European Commission with the goal of making Europe's cultural and scientific heritage accessible to the public. ASSETS is a two-year Best Practice Network co-funded by the CIP PSP Programme to improve performance, accessibility and usability of the Europeana search engine. Here we present a characterization of the Europeana logs by showing statistics on common behavioral patterns of the Europeana users.Source: ERCIM news 86 (2011): 39–40.
Ceccarelli D., Gordea S., Lucchese C., Nardini F. M., Perego R. Tolomei G.
Europeana is a strategic project funded by the European Commission with the goal of making Europe's cultural and scientific heritage accessible to the public. ASSETS is a two-year Best Practice Network co-funded by the CIP PSP Programme to improve performance, accessibility and usability of the Europeana search engine. Here we present a characterization of the Europeana logs by showing statistics on common behavioral patterns of the Europeana users.Source: ERCIM news 86 (2011): 39–40.
See at:
ercim-news.ercim.eu | CNR ExploRA
2013
Conference article
Restricted
Modeling and predicting the task-by-task behavior of search engine users
Lucchese C., Orlando S., Perego R., Tolomei G., Silvestri F.
Web search engines answer user needs on a query-by-query fashion, namely they retrieve the set of the most relevant results to each issued query, independently. However, users often submit queries to perform multiple, related tasks. In this paper, we first discuss a methodology to discover from query logs the latent tasks performed by users. Furthermore, we introduce the Task Relation Graph (TRG) as a representation of users' search behaviors on a task-by-task perspective. The task-by-task behavior is captured by weighting the edges of TRG with a relatedness score computed between pairs of tasks, as mined from the query log. We validate our approach on a concrete application, namely a task recommender system, which suggests related tasks to users on the basis of the task predictions derived from the TRG. Finally, we show that the task recommendations generated by our solution are beyond the reach of existing query suggestion schemes, and that our method recommends tasks that user will likely perform in the near future.Source: OAIR 2013 - 10th Conference on Open Research Areas in Information Retrieval, pp. 77–84, Lisbon, Portugal, 15-17 May 2013
Lucchese C., Orlando S., Perego R., Tolomei G., Silvestri F.
Web search engines answer user needs on a query-by-query fashion, namely they retrieve the set of the most relevant results to each issued query, independently. However, users often submit queries to perform multiple, related tasks. In this paper, we first discuss a methodology to discover from query logs the latent tasks performed by users. Furthermore, we introduce the Task Relation Graph (TRG) as a representation of users' search behaviors on a task-by-task perspective. The task-by-task behavior is captured by weighting the edges of TRG with a relatedness score computed between pairs of tasks, as mined from the query log. We validate our approach on a concrete application, namely a task recommender system, which suggests related tasks to users on the basis of the task predictions derived from the TRG. Finally, we show that the task recommendations generated by our solution are beyond the reach of existing query suggestion schemes, and that our method recommends tasks that user will likely perform in the near future.Source: OAIR 2013 - 10th Conference on Open Research Areas in Information Retrieval, pp. 77–84, Lisbon, Portugal, 15-17 May 2013
See at:
dl.acm.org | CNR ExploRA
2012
Other
Unknown
S-cube
Silvestri F., Nardini F. M., Baraglia R., Tolomei G., Capannini G., Giordano M., Di Napoli C., Lombardi S.
Contract No 215483 Funded by the Commission of European Communities Information Society and Media Directorate-General, the project mission is to establish a unified, multidisciplinary, vibrant research community which will enable Europe to lead the software-services revolution and help shape the software service based Internet which will underpin the whole of our future society. S-Cube aims to push the frontiers of research in Service Oriented Computing by creating a vigorous research agenda where knowledge from diverse research communities is meaningfully synthesized, integrated and applied. Starting on March, 1 2008.Project(s): S-CUBE
Silvestri F., Nardini F. M., Baraglia R., Tolomei G., Capannini G., Giordano M., Di Napoli C., Lombardi S.
Contract No 215483 Funded by the Commission of European Communities Information Society and Media Directorate-General, the project mission is to establish a unified, multidisciplinary, vibrant research community which will enable Europe to lead the software-services revolution and help shape the software service based Internet which will underpin the whole of our future society. S-Cube aims to push the frontiers of research in Service Oriented Computing by creating a vigorous research agenda where knowledge from diverse research communities is meaningfully synthesized, integrated and applied. Starting on March, 1 2008.Project(s): S-CUBE
See at: CNR ExploRA