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2005 Article Unknown

Digital Library Information - Technology Infrastructure
Ioannidis Y., Maier D., Abiteboul S., Buneman P., Davidson S., Fox E., Halevy A., Knoblock C., Rabitti F., Schek H., Weikum G.
This paper charts a research agenda on systems-oriented issues in digital libraries. It focuses on the most central and generic system issues, including system architecture, user-level functionality, and the overall operational environment. With respect to user- level functionality, in particular, it abstracts the overall information lifecycle in digital libraries to five major stages and identifies key research problems that require solution in each stage. Finally, it recommends an explicit set of activities that would help achieve the research goals outlined and identifies several dimensions along which progress of the digital library field can be evaluatedSource: International journal on digital libraries (Print) 5 (2005): 266–274. doi:10.1007/s00799-004-0094-8
DOI: 10.1007/s00799-004-0094-8

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2007 Report Unknown

SAPIR Publications - D9.3
Rabitti F.
This report presents the result of the SAPIR project in the first year, in terms of scientific publications. According to the DOW, the report describes project activities undertaken during the first year of the project, as part of task T9.3. The activity of publishing papers is considered particularly important for the project since it is both an important way of disseminating project results in the research community and a way of receiving valuable feed-backs. Moreover, for this first report on the project scientific publications, we decided to add a list of papers, published by the project partners before the beginning of the project, which constitute the basis of the project itself.

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2010 Conference object Unknown

Scalability issues for self similarity join in distributed systems
Gennaro C., Rabitti F.
Efficient processing of similarity joins is important for a large class of data analysis and data-mining applications. This primitive finds all pairs of records within a predefined distance threshold of each other. However, most of the existing approaches have been based on spatial join techniques designed primarily for data in a vector space. Treating data collections as metric objects brings a great advantage in generality, because a single metric technique can be applied to many specific search problems quite different in nature. In this paper, we concentrate our attention on a special form of join, the Self Similarity Join, which retrieves pairs from the same dataset. In particular, we consider the case in which the dataset is split into subsets that are searched for self similarity join independently (e.g, in a distributed computing environment). To this end, we formalize the abstract concept of epsilon-Cover, prove its correctness, and demonstrate its effectiveness by applying it to two real implementations on a real-life large dataset.Source: The 18th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp. 309–316, Pisa, 17-19 February 2010
DOI: 10.1109/PDP.2010.73

See at: DOI Resolver | ieeexplore.ieee.org | CNR People


2007 Conference object Unknown

The Web database of Florentine coats of arms. A project of identify complex image content using both indexing and pattern recognition
Falchi F., Rabitti F., Schweibenz W., Simane J.
The paper describes a collection of Florentine coats of arms, which was digitised and made accessible on the Web. In addition to the traditional approach of textual description and indexing, an additional retrieval mode was chosen based on the visual specification by users of the content of images representing the coat of arms. This seems an interesting alternative for two reasons. Firstly, the texts of the database are only available in German language. Secondly, heraldry uses a specific and complex terminology which makes the textual approach difficult for laypersons. Therefore an additional visual approach seems to be an interesting solution for an international audience.Source: Electronic Imaging & the Visual Arts. EVA 2007, pp. 187–192, Florence, Italy, March 26-30 2007

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2007 Conference object Unknown

Florentine coats of arms on the Web: experimenting retrieval based on text or image content
Falchi F., Rabitti F., Schweibenz W., Simane J.
The paper describes two different ways of accessing a collection of Florentine coats of arms, which was digitised and made available on the Web. One way is a traditional approach: textual description and indexing. As heraldry uses a specific and complex terminology the textual approach seemed alright for experts but insufficient for laypersons. Therefore an additional retrieval mode was chosen which is based on the visual specification by users of the content of images representing the coat of arms. This access mode allows users who are not familiar with heraldry to access the collection.Source: Open Innovation. Neue Perspektiven im Kontext von Information und Wissen. Beiträge des 10. Internationalen Symposiums für Informationswissenschaft (ISI 2007) und der 13. Jahrestagung der IuK-Initiative Wissenschaft, pp. 1–12, Köln, Germany, May 30 - June 1 2007

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2017 Conference object Unknown

High-dimensional simplexes for supermetric search
Connor R., Vadicamo L., Rabitti F.
In a metric space, triangle inequality implies that, for any three objects, a triangle with edge lengths corresponding to their pairwise distances can be formed. The n-point property is a generalisation of this where, for any (n+1) objects in the space, there exists an n-dimensional simplex whose edge lengths correspond to the distances among the objects. In general, metric spaces do not have this property; however in 1953, Blumenthal showed that any semi-metric space which is isometrically embeddable in a Hilbert space also has the n-point property. We have previously called such spaces supermetric spaces, and have shown that many metric spaces are also supermetric, including Euclidean, Cosine, Jensen-Shannon and Triangular spaces of any dimension. Here we show how such simplexes can be constructed from only their edge lengths, and we show how the geometry of the simplexes can be used to determine lower and upper bounds on unknown distances within the original space. By increasing the number of dimensions, these bounds converge to the true distance. Finally we show that for any Hilbert-embeddable space, it is possible to construct Euclidean spaces of arbitrary dimensions, from which these lower and upper bounds of the original space can be determined. These spaces may be much cheaper to query than the original. For similarity search, the engineering tradeoffs are good: we show significant reductions in data size and metric cost with little loss of accuracy, leading to a significant overall improvement in exact search performance.Source: SISAP 2017 - Similarity Search and Applications. 10th International Conference, pp. 96–109, Munich, Germany, 4-6 October 2017
DOI: 10.1007/978-3-319-68474-1_7

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2007 Conference object Unknown

Infrastructures for scalable multimedia search
Rabitti F., Zezula P.
This presentation illustrates the objectives of the SAPIR Project and how the project is approaching them. Project's objective are: i) Develop cutting-edge technology to index and search large scale audio-visual information by content. ii) Make information available on many devices, enhanced by social networking while keeping privacy and preventing fraud. iii) Support new trends in MM content production: personal producer VS professional producers.Source: European Information Space: Infrastructures, Services and Applications Workshop, Rome, Italy, 29-30 October 2007

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2013 Article Unknown

A mediator-based approach for integrating heterogeneous multimedia sources
Beneventano D., Gennaro C., Bergamaschi S., Rabitti F.
In many applications, the information required by the user cannot be found in just one source, but has to be retrieved from many varying sources. This is true not only of formatted data in database management systems, but also of textual documents and multimedia data, such as images and videos. We propose a mediator system that provides the end-user with a single query interface to an integrated view of multiple heterogeneous data sources. We exploit the capabilities of the MOMIS integration system and the MILOS multimedia data management system. Each multimedia source is managed by an instance of MILOS, in which a collection of multimedia records is made accessible by means of similarity searches employing the query-by-example paradigm. MOMIS provides an integrated virtual view of the underlying multimedia sources, thus offering unified multimedia access services. Two features are that MILOS is flexible--it is not tied to any particular similarity function--and the MOMIS's mediator query processor only exploits the ranks of the local answers.Source: Multimedia tools and applications 62 (2013): 427–450. doi:10.1007/s11042-011-0904-0
DOI: 10.1007/s11042-011-0904-0

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2014 Conference object Unknown

Some theoretical and experimental observations on permutation spaces and similarity search
Amato G., Falchi F., Rabitti F., Vadicamo L.
Permutation based approaches represent data objects as ordered lists of predefined reference objects. Similarity queries are executed by searching for data objects whose permutation representation is similar to the query one. Various permutation-based indexes have been recently proposed. They typically allow high efficiency with acceptable effectiveness. Moreover, various parameters can be set in order to find an optimal trade-off between quality of results and costs. In this paper we studied the permutation space without referring to any particular index structure focusing on both theoretical and experimental aspects. We used both synthetic and real-word datasets for our experiments. The results of this work are relevant in both developing and setting parameters of permutation-based similarity searching approaches.Source: SISAP 2014 - Similarity Search and Applications. 7th International Conference, pp. 37–49, Los Cabos, Mexico, 29-31 Ottobre 2014
DOI: 10.1007/978-3-319-11988-5_4

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2008 Conference object Unknown

A metric cache for similarity search
Lucchese C., Perego R., Rabitti F., Falchi F., Orlando S.
Similarity search in metric spaces is a general paradigm that can be used in several application elds. It can also be ef- fectively exploited in content-based image retrieval systems, which are shifting their target towards theWeb-scale dimen- sion. In this context, an important issue becomes the design of scalable solutions, which combine parallel and distributed architectures with caching at several levels. To this end, we investigate the design of a similarity cache that works in metric spaces. It is able to answer with exact and approximate results: even when an exact match is not present in cache, our cache may return an approximate re- sult set with quality guarantees. By conducting tests on a collection of one million high-quality digital photos, we show that the proposed caching techniques can have a signi cant impact on performance, like caching on text queries has been proved e ective for traditional Web search engines.Source: Sixth Workshop on Large-Scale Distributed Systems for Information Retrieval, pp. 43–50, Napa Valley, California, US, 26-30 October 2008
DOI: 10.1145/1458469.1458473

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2014 Conference object Unknown

Aggregating local descriptors for epigraphs recognition
Amato G., Falchi F., Rabitti F., Vadicamo L.
In this paper, we consider the task of recognizing epigraphs in images such as photos taken using mobile devices. Given a set of 17,155 photos related to 14,560 epigraphs, we used a k-NearestNeighbor approach in order to perform the recognition. The contribution of this work is in evaluating state-of-the-art visual object recognition techniques in this specific context. The experimental results conducted show that Vector of Locally Aggregated Descriptors obtained aggregating SIFT descriptors is the best choice for this task.Source: The Fourth International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage, pp. 49–58, Veliko Tarnovo, Bulgaria, 18-21 September 2014
Project(s): EAGLE

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2017 Article Unknown

Hilbert exclusion: improved metric search through finite isometric embeddings
Connor R., Cardillo F. A., Vadicamo L., Rabitti F.
Most research into similarity search in metric spaces relies on the triangle inequality property. This property allows the space to be arranged according to relative distances to avoid searching some subspaces. We show that many common metric spaces, notably including those using Euclidean and Jensen-Shannon distances, also have a stronger property, sometimes called the four-point property: In essence, these spaces allow an isometric embedding of any four points in three-dimensional Euclidean space, as well as any three points in two-dimensional Euclidean space. In fact, we show that any space that is isometrically embeddable in Hilbert space has the stronger property. This property gives stronger geometric guarantees, and one in particular, which we name the Hilbert Exclusion property, allows any indexing mechanism which uses hyperplane partitioning to perform better. One outcome of this observation is that a number of state-of-the-art indexing mechanisms over high-dimensional spaces can be easily refined to give a significant increase in performance; furthermore, the improvement given is greater in higher dimensions. This therefore leads to a significant improvement in the cost of metric search in these spaces.Source: ACM transactions on information systems 35 (2017): 17–27. doi:10.1145/3001583
DOI: 10.1145/3001583

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2007 Other Unknown

VICE Comunità Virtuali per l'Educazione - Progetto MIUR
Bolettieri P., Gennaro C., Rabitti F.
Il progetto si propone di sviluppare una piattaforma innovativa per la messa a punto di applicazioni di formazione, fruibili dove e quando necessario, anche a distanza, con elevato supporto tecnologico. Il progetto affronta uno dei temi applicativi socialmente e tecnicamente più interessanti per i prossimi anni sarà sicuramente quello dalla e-formazione: formazione offerta a professionisti ed aziende, con paradigmi di business e con strumenti tecnologici tipici della e-economy. La continua innovazione della società (in senso organizzativo, economico, tecnologico, ecc.) rende evidente la necessità di non più considerare la formazione, anche ad alto od altissimo livello, come terminata alla fine del ciclo “canonico” di studi (sia esso un diploma, una laurea, una laurea specialistica o, addirittura, un dottorato). E’ pertanto necessario sviluppare infrastrutture organizzative, metodologiche e tecnologiche perché sia possibile una formazione continua a professionisti e personale inserito in aziende, per tutto il resto della loro vita professionale.

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2007 Conference object Unknown

A distributed incremental nearest neighbor algorithm
Falchi F., Gennaro C., Rabitti F., Zezula P.
Searching for non-text data (e.g., images) is mostly done by means of metadata annotations or by extracting the text close to the data. However, supporting real content-based audio-visual search, based on similarity search on features, is significantly more expensive than searching for text. Moreover, the search exhibits linear scalability with respect to the data set size. In this paper, we present a Distributed Incremental Nearest Neighbor algorithm (DINN) for finding nearest neighbor in an incremental fashion over data distributed between nodes which are able to perform a local Incremental Nearest Neighbor (local-INN). We prove that our algorithm is optimal with respect to both number of involved nodes and number of local-INN invocations. An implementation of our DINN algorithm, on a real P2P system called MCAN, was used for conducting an extensive experimental evaluation on a real-life dataset.Source: 2nd international conference on Scalable information systems. Infoscale'07, Suzhou, China, June 6-8 2007
DOI: 10.1145/1366804.1366910

See at: dl.acm.org | DOI Resolver | CNR People


2006 Part of book or chapter of book Unknown

MILOS: un sistema di content management per lo sviluppo di biblioteche digitali
Amato G., Gennaro C., Savino P., Rabitti F.
Digital Libraries (DL) are becoming widely used for the archival and management of many different types of digital objects. Depending on the application environment, they provide different functionality such as the management of different media (like images and audio/video), the use of specific metadata models, the support of retrieval based on object's structure or content, etc. In this paper we address the problem of an efficient development of a Digital Library. Our claim is that the development of ad-hoc software modules for each new DL is not effective, while it is advantageous to develop and use a general purpose Content Management System (CMS). We propose the use of the MILOS Multimedia Content Management System which supports the storage and content based retrieval of any multimedia documents whose descriptions are provided by using arbitrary metadata models represented in XML. The paper also illustrates the experiments performed by using the MILOS system to build DLs belonging to four different and heterogeneous collections which contain news, scientific papers, and audio/video documentaries.Source: , pp. 146–157. Roma: AIB, 2006

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2016 Conference object Unknown

Supermetric search with the four-point property
Connor R., Vadicamo L., Cardillo F. A., Rabitti F.
Metric indexing research is concerned with the efficient evaluation of queries in metric spaces. In general, a large space of objects is arranged in such a way that, when a further object is presented as a query, those objects most similar to the query can be efficiently found. Most such mechanisms rely upon the triangle inequality property of the metric governing the space. The triangle inequality property is equivalent to a finite embedding property, which states that any three points of the space can be isometrically embedded in two-dimensional Euclidean space. In this paper, we examine a class of semimetric space which is finitely 4-embeddable in three-dimensional Euclidean space. In mathematics this property has been extensively studied and is generally known as the four-point property. All spaces with the four-point property are metric spaces, but they also have some stronger geometric guarantees. We coin the term supermetric space as, in terms of metric search, they are significantly more tractable. We show some stronger geometric guarantees deriving from the four-point property which can be used in indexing to great effect, and show results for two of the SISAP benchmark searches that are substantially better than any previously published.Source: Similarity Search and Applications. 9th International Conference, pp. 51–64, Tokyo, Japan, 24-26 October 2016
DOI: 10.1007/978-3-319-46759-7_4

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2003 Article Unknown

Region proximity in metric spaces and its use for approximate similarity search
Amato G., Rabitti F., Savino P., Zezula P.
Similarity search structures for metric data typically bound object partitions by ball regions. Since regions can overlap, a relevant issue is to estimate the proximity of regions in order to predict the number of objects in the regions' intersection. The paper analyzes the problem by using a probabilistic approach and provides a solution that effectively computes the proximity through realistic heuristics that only require small amounts of auxiliary data. An extensive simulation to validate the technique is provided. An application is then developed to demonstrate how the proximity measure can be successfully applied to the approximate similarity search. Search speedup is achieved by ignoring data regions whose proximity with the query region is smaller than a user defined threshold. This idea is implemented in a metric tree environment for the similarity range and nearest neighbors queries. Several measures of efficiency and effectiveness are applied to evaluate proposed approximate search algorithms on real-life data sets. Improvements of two orders of magnitude are achieved for moderately approximated search results. We demonstrate that the precision of proximity measures can significantly influence the quality of approximated algorithms.Source: ACM transactions on information systems 21 (2003): 192–227. doi:10.1145/763693.763696
DOI: 10.1145/763693.763696

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2013 Part of book or chapter of book Restricted

Quick and Easy Implementation of Approximate Similarity Search with Lucene
Amato G., Bolettieri P., Gennaro C., Rabitti F.
Similarity search technique has been proved to be an effective way for retrieving multimedia content. However, as the amount of available multimedia data increases, the cost of developing from scratch a robust and scalable system with content-based image retrieval facilities is quite prohibitive. In this paper, we propose to exploit an approach that allows us to convert low level features into a textual form. In this way, we are able to easily set up a retrieval system on top of the Lucene search engine library that combines full-text search with approximate similarity search capabilities.Source: Digital Libraries and Archives. 8th Italian Research Conference. IRCDL 2012. Revised Selected Papers, edited by Agosti M., Esposito F., Ferilli S., Ferro, N., pp. 163–171, 2013
DOI: 10.1007/978-3-642-35834-0_17

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2007 Article Unknown

The SAPIR Project: Executing A/V Complex Queries in Peer-to-Peer Systems
Gennaro C., Perego R., Rabitti F.
Searching for non-text data (eg, images) is mostly done by means of metadata annotations or by extracting the text close to the data. However, supporting real content-based audio-visual search, based on similarity search on features, is significantly more expensive than searching for text. Moreover, the search exhibits linear scalability with respect to the data set size. The European project SAPIR is currently addressing this problem.Source: ERCIM news 70 (2007): 62–63.

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2016 Conference object Unknown

Indexing 100M images with deep features and MI-File
Amato G, Falchi F, Gennaro C, Rabitti F.
In the context of the Multimedia Commons initiative, we extracted and indexed deep features of about 100M images uploaded on Flickr between 2004 and 2014 and published under a Creative Commons commercial or noncommercial license. The extracted features and an online demo built using the MI-File approximated data structure are both publicly available. The online CBIR system demonstrates the effectiveness of the deep features and the efficiency of the indexing approach.Source: Italian Information Retrieval Workshop, Venezia, Italy, 30-31 May 2016

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