2010
Report
Unknown
VISITO - Componenti per l'estrazione delle features dalle immagini
Lucchese C., Venturini R.
La ricerca efficiente di informazioni utilizza tecniche di indicizzazione dei dati al fine di soddisfare efficientemente ed efficacemente le interrogazioni sottomesse dagli utenti. In pratica gli indici rappresentano un'astrazione delle informazioni basata su bag-of-feature, l'insieme cioè delle caratteristiche più importanti (feature) di un generico oggetto, sia esso un documento testuale o un oggettomultimedialequaleunafotografiadigitale. Esistononumerositipidifeatureassociatiadun'immagineelaloroestrazione,effettuataconappositi software,écomputazionalmentecostosa.Seilnumerodiimmaginiègrande,iltempototalerichiestosuun computertradizionalediventaproibitivo.Importante,èperòporrel'accentosulfattocheogniimmagineha uninsiemedicaratteristichechenondipendedallealtreimmagini.Conseguenzadiquesto fattoèche si possonodisegnaretecnicheefficientidifeatureextractionbasatesutecnichedicalcoloparallelo.Loscopo diquestaattivitàèquindiquellodisvilupparecomponentiincuil'estrazionedifeaturesiaresaefficiente usandotecnologiedicalcoloadalteprestazioniallostatodell'artequali,adesempio,cloudcomputing. Inquestodocumento,vengonoillustratelefeaturediinteresseperilprogettoVISITO,evienedescrittoil softwaresviluppatoperlaloroestrazione.Abbiamopreferito,essendoquestoundeliverableprettamente tecnico,redigereilrestodeldocumentoinlinguainglese.Source: Project report, VISITO Tuscany, 2010
Lucchese C., Venturini R.
La ricerca efficiente di informazioni utilizza tecniche di indicizzazione dei dati al fine di soddisfare efficientemente ed efficacemente le interrogazioni sottomesse dagli utenti. In pratica gli indici rappresentano un'astrazione delle informazioni basata su bag-of-feature, l'insieme cioè delle caratteristiche più importanti (feature) di un generico oggetto, sia esso un documento testuale o un oggettomultimedialequaleunafotografiadigitale. Esistononumerositipidifeatureassociatiadun'immagineelaloroestrazione,effettuataconappositi software,écomputazionalmentecostosa.Seilnumerodiimmaginiègrande,iltempototalerichiestosuun computertradizionalediventaproibitivo.Importante,èperòporrel'accentosulfattocheogniimmagineha uninsiemedicaratteristichechenondipendedallealtreimmagini.Conseguenzadiquesto fattoèche si possonodisegnaretecnicheefficientidifeatureextractionbasatesutecnichedicalcoloparallelo.Loscopo diquestaattivitàèquindiquellodisvilupparecomponentiincuil'estrazionedifeaturesiaresaefficiente usandotecnologiedicalcoloadalteprestazioniallostatodell'artequali,adesempio,cloudcomputing. Inquestodocumento,vengonoillustratelefeaturediinteresseperilprogettoVISITO,evienedescrittoil softwaresviluppatoperlaloroestrazione.Abbiamopreferito,essendoquestoundeliverableprettamente tecnico,redigereilrestodeldocumentoinlinguainglese.Source: Project report, VISITO Tuscany, 2010
See at: CNR ExploRA
2010
Report
Unknown
VISITO - Sviluppo del componente per l'indicizzazione dei dati
Lucchese C., Venturini R.
Lo scopo del sistema per la gestione dei dati è quello di permettere il recupero veloce ed efficiente dei metadati associati ai Punti di Interesse turistico (PoI) e alle foto. In questo documento, vengono descritti i metadati associati ai PoI e alle foto e presentate le funzionalità fornite dal sistema implementato. Per ciascuna di esse vengono ampiamente descritte le strategie e gli strumenti utilizzati per la sua implementazione.Source: Project report, VISITO Tuscany, 2010
Lucchese C., Venturini R.
Lo scopo del sistema per la gestione dei dati è quello di permettere il recupero veloce ed efficiente dei metadati associati ai Punti di Interesse turistico (PoI) e alle foto. In questo documento, vengono descritti i metadati associati ai PoI e alle foto e presentate le funzionalità fornite dal sistema implementato. Per ciascuna di esse vengono ampiamente descritte le strategie e gli strumenti utilizzati per la sua implementazione.Source: Project report, VISITO Tuscany, 2010
See at: CNR ExploRA
2010
Report
Unknown
VISITO Tuscany - Progetto dell'architettura della piattaforma VISITO Tuscany v1
Atzori M., Bazzoni G., Bolettieri P., La Torre F., Loschiavo D., Lucchese C., Manfrin S., Martinelli F., Melani A., Naldi C., Pironi A., Rubichi A., Venturini R., Zanetti N.
Il documento è inquadrato nell'Obiettivo Operativo 2 del Progetto VISITO Tuscany, nel quale viene elaborata la progettazione dell'intero sistema. In particolare in questo documento verrà descritta l'architettura del sistema sulla base del Reference Model for Open Distributed Processing (RM-ODP)che prevede cinque viste: enterprise, information, computational, engineering e technology.Source: Project report, VISITO Tuscany, 2010
Atzori M., Bazzoni G., Bolettieri P., La Torre F., Loschiavo D., Lucchese C., Manfrin S., Martinelli F., Melani A., Naldi C., Pironi A., Rubichi A., Venturini R., Zanetti N.
Il documento è inquadrato nell'Obiettivo Operativo 2 del Progetto VISITO Tuscany, nel quale viene elaborata la progettazione dell'intero sistema. In particolare in questo documento verrà descritta l'architettura del sistema sulla base del Reference Model for Open Distributed Processing (RM-ODP)che prevede cinque viste: enterprise, information, computational, engineering e technology.Source: Project report, VISITO Tuscany, 2010
See at: CNR ExploRA
2010
Report
Unknown
VISITO Tuscany - Rapporto con la specifica dettagliata delle funzionalità della piattaforma VISITO Tuscany
Bolettieri P., Benedetti L., La Torre F., Loschiavo D., Lucchese C., Lungarotti F., Salvadori S., Scopigno R., Venturini R.
Questo documento è il rapporto con la specifica dettagliata delle funzionalità svolta all'interno del Progetto VISITO Tuscany a partire dal mese 4 fino al mese 5 nell'ambito dell'Obbiettivo Operativo 2, Attività A2.1 "Rapporto con la specifica dettagliata delle funzionalità della piattaforma Visito Tuscany". Il rapporto descriverà dettagliatamente le funzionalità offerte dal sistema, ponendo particolare attenzione nell'identificare funzionalità, di notevole importanza per i potenziali utenti, che non sono tuttora fornite da altri sistemi e che potranno essere realizzate capitalizzando sulla sinergia dei membri del consorzio del progetto e sulle loro attività pregresse.Source: Project report, VISITO Tuscany, 2010
Bolettieri P., Benedetti L., La Torre F., Loschiavo D., Lucchese C., Lungarotti F., Salvadori S., Scopigno R., Venturini R.
Questo documento è il rapporto con la specifica dettagliata delle funzionalità svolta all'interno del Progetto VISITO Tuscany a partire dal mese 4 fino al mese 5 nell'ambito dell'Obbiettivo Operativo 2, Attività A2.1 "Rapporto con la specifica dettagliata delle funzionalità della piattaforma Visito Tuscany". Il rapporto descriverà dettagliatamente le funzionalità offerte dal sistema, ponendo particolare attenzione nell'identificare funzionalità, di notevole importanza per i potenziali utenti, che non sono tuttora fornite da altri sistemi e che potranno essere realizzate capitalizzando sulla sinergia dei membri del consorzio del progetto e sulle loro attività pregresse.Source: Project report, VISITO Tuscany, 2010
See at: CNR ExploRA
2010
Journal article
Open Access
On compact representations of all-pairs-shortest-path-distance matrices
Ferragina P., Nitto I., Venturini R.
Let G be an unweighted and undirected graph of n nodes, and let be the n×n matrix storing the All-Pairs-Shortest-Path Distances in G. Since contains integers in [n] U +∞, its plain storage takes n. log(n+1) bits. However, a simple counting argument shows that n. /2 bits are necessary to store . In this paper we investigate the question of finding a succinct representation of that requires O(n. ) bits of storage and still supports constant-time access to each of its entries. This is asymptotically optimal in the worst case, and far from the information-theoretic lower bound by a multiplicative factor log_2 3. As a result O(1) bits per pairs of nodes in G are enough to retain constant-time access to their shortest-path distance. We achieve this result by reducing the storage of to the succinct storage of labeled trees and ternary sequences, for which we properly adapt and orchestrate the use of known compressed data structures. This approach can be easily and optimally extended to graphs whose edge weights are positive integers bounded by a constant value.Source: Theoretical computer science 411 (2010): 3293–3300. doi:10.1016/j.tcs.2010.05.021
DOI: 10.1016/j.tcs.2010.05.021
Metrics:
Ferragina P., Nitto I., Venturini R.
Let G be an unweighted and undirected graph of n nodes, and let be the n×n matrix storing the All-Pairs-Shortest-Path Distances in G. Since contains integers in [n] U +∞, its plain storage takes n. log(n+1) bits. However, a simple counting argument shows that n. /2 bits are necessary to store . In this paper we investigate the question of finding a succinct representation of that requires O(n. ) bits of storage and still supports constant-time access to each of its entries. This is asymptotically optimal in the worst case, and far from the information-theoretic lower bound by a multiplicative factor log_2 3. As a result O(1) bits per pairs of nodes in G are enough to retain constant-time access to their shortest-path distance. We achieve this result by reducing the storage of to the succinct storage of labeled trees and ternary sequences, for which we properly adapt and orchestrate the use of known compressed data structures. This approach can be easily and optimally extended to graphs whose edge weights are positive integers bounded by a constant value.Source: Theoretical computer science 411 (2010): 3293–3300. doi:10.1016/j.tcs.2010.05.021
DOI: 10.1016/j.tcs.2010.05.021
Metrics:
See at:
Theoretical Computer Science 
| www.sciencedirect.com 
| CNR ExploRA
2010
Journal article
Restricted
The compressed permuterm index
Ferragina P., Venturini R.
The Permuterm index [Garfield 1976] is a time-efficient and elegant solution to the string dictionary problem in which pattern queries may possibly include one wild-card symbol (called Tolerant Retrieval problem). Unfortunately the Permuterm index is space inefficient because it quadruples the dictionary size. In this article we propose the Compressed Permuterm Index which solves the Tolerant Retrieval problem in time proportional to the length of the searched pattern, and space close to the kth order empirical entropy of the indexed dictionary. We also design a dynamic version of this index that allows to efficiently manage insertion in, and deletion from, the dictionary of individual strings. The result is based on a simple variant of the Burrows-Wheeler Transform, defined on a dictionary of strings of variable length, that allows to efficiently solve the Tolerant Retrieval problem via known (dynamic) compressed indexes [Navarro and Mäkinen 2007]. We will complement our theoretical study with a significant set of experiments that show that the Compressed Permuterm Index supports fast queries within a space occupancy that is close to the one achievable by compressing the string dictionary via gzip or bzip. This improves known approaches based on Front-Coding [Witten et al. 1999] by more than 50% in absolute space occupancy, still guaranteeing comparable query time.Source: ACM transactions on algorithms 7 (2010): 10–21. doi:10.1145/1868237.1868248
DOI: 10.1145/1868237.1868248
Metrics:
Ferragina P., Venturini R.
The Permuterm index [Garfield 1976] is a time-efficient and elegant solution to the string dictionary problem in which pattern queries may possibly include one wild-card symbol (called Tolerant Retrieval problem). Unfortunately the Permuterm index is space inefficient because it quadruples the dictionary size. In this article we propose the Compressed Permuterm Index which solves the Tolerant Retrieval problem in time proportional to the length of the searched pattern, and space close to the kth order empirical entropy of the indexed dictionary. We also design a dynamic version of this index that allows to efficiently manage insertion in, and deletion from, the dictionary of individual strings. The result is based on a simple variant of the Burrows-Wheeler Transform, defined on a dictionary of strings of variable length, that allows to efficiently solve the Tolerant Retrieval problem via known (dynamic) compressed indexes [Navarro and Mäkinen 2007]. We will complement our theoretical study with a significant set of experiments that show that the Compressed Permuterm Index supports fast queries within a space occupancy that is close to the one achievable by compressing the string dictionary via gzip or bzip. This improves known approaches based on Front-Coding [Witten et al. 1999] by more than 50% in absolute space occupancy, still guaranteeing comparable query time.Source: ACM transactions on algorithms 7 (2010): 10–21. doi:10.1145/1868237.1868248
DOI: 10.1145/1868237.1868248
Metrics:
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dl.acm.org | ACM Transactions on Algorithms | CNR ExploRA
2010
Conference article
Unknown
VSEncoding: efficient coding and fast decoding of integer lists via dynamic programming
Silvestri F., Venturini R.
Encoding lists of integers efficiently is important for many applications in different fields. Adjacency lists of large graphs are usually encoded to save space and to improve decoding speed. Inverted indexes of Information Retrieval systems keep the lists of postings compressed in order to exploit the memory hierarchy. Secondary indexes of DBMSs are stored similarly to inverted indexes in IR systems. In this paper we propose Vector of Splits Encoding (VSEncoding), a novel class of encoders that work by optimally partitioning a list of integers into blocks which are efficiently compressed by using simple encoders. In previous works heuristics were applied during the partitioning step. Instead, we find the optimal solution by using a dynamic programming approach. Experiments show that our class of encoders outperform all the existing methods in literature by more than 10% (with the exception of Binary Interpolative Coding with which they, roughly, tie) still retaining a very fast decompression algorithm.Source: Conference on Information and Knowledge Management, pp. 1219–1228, Toronto, Canada, 27 ottobre 2010
Silvestri F., Venturini R.
Encoding lists of integers efficiently is important for many applications in different fields. Adjacency lists of large graphs are usually encoded to save space and to improve decoding speed. Inverted indexes of Information Retrieval systems keep the lists of postings compressed in order to exploit the memory hierarchy. Secondary indexes of DBMSs are stored similarly to inverted indexes in IR systems. In this paper we propose Vector of Splits Encoding (VSEncoding), a novel class of encoders that work by optimally partitioning a list of integers into blocks which are efficiently compressed by using simple encoders. In previous works heuristics were applied during the partitioning step. Instead, we find the optimal solution by using a dynamic programming approach. Experiments show that our class of encoders outperform all the existing methods in literature by more than 10% (with the exception of Binary Interpolative Coding with which they, roughly, tie) still retaining a very fast decompression algorithm.Source: Conference on Information and Knowledge Management, pp. 1219–1228, Toronto, Canada, 27 ottobre 2010
See at: CNR ExploRA
2010
Other
Unknown
POR FESR 2007-2013 VISITO Tuscany project: VIsual Support to Interactive TOurism in Tuscany
Lucchese C., Venturini R., Dazzi P., Ferrini R., Perego R., Baraglia R., Tonellotto N., Versienti L.
The project aims to create an infrastructure providing a user-centric fruition of the artistic and cultural heritage present in the art cities of Tuscany. The system that has to be realized will be able to manage in an integrated manner both historical-artistic information and other visitors interest requests. In particular, the project aims to develop advanced technologies to manage photographic materials which deal with the cultural heritage present in the Tuscan cities of art in order to realize a personalized electronic guide designed to provide better use and access to our artistic heritage. The goal is to offer novel immersive touristic services through both the new generation of mobile devices and the Internet. Pilot tests are planned to be conducted in the cities of Florence, Pisa and San Gimignano in order to test the developed system.
Lucchese C., Venturini R., Dazzi P., Ferrini R., Perego R., Baraglia R., Tonellotto N., Versienti L.
The project aims to create an infrastructure providing a user-centric fruition of the artistic and cultural heritage present in the art cities of Tuscany. The system that has to be realized will be able to manage in an integrated manner both historical-artistic information and other visitors interest requests. In particular, the project aims to develop advanced technologies to manage photographic materials which deal with the cultural heritage present in the Tuscan cities of art in order to realize a personalized electronic guide designed to provide better use and access to our artistic heritage. The goal is to offer novel immersive touristic services through both the new generation of mobile devices and the Internet. Pilot tests are planned to be conducted in the cities of Florence, Pisa and San Gimignano in order to test the developed system.
See at: CNR ExploRA
2010
Report
Open Access
VSEncoding: efficient coding and fast decoding of integer lists via dynamic programming
Silvestri F., Venturini R.
Encoding lists of integers in an efficient manner is key task in many applications in different fields. Adjacency lists of large graphs are usually encoded to save space and to im- prove decoding speed. Inverted indexes of Information Re- trieval systems keep the lists of postings usually compressed to allow an optimal utilization of memory hierarchy. Sec- ondary indexes of DBMS's are stored similarly to inverted indexes in IR systems. In this paper we propose a novel class of encoders (called VSEncoding from Vector of Splits Encoding) that, roughly speaking, work by partitioning an list of integers into blocks which are efficiently compressed by using simple encoders. Differently from previous work where heuristics were applied during the partitioning step, we carry out this important step via dynamic programming, which leads to produce the optimal solution. Experiments show that our class of encoders outperform all the existing methods in literature by more than 10% (with the exception of Binary Interpolative Coding with which they, roughly, tie) still retaining very fast decompression.Source: ISTI Technical reports, 2010
Silvestri F., Venturini R.
Encoding lists of integers in an efficient manner is key task in many applications in different fields. Adjacency lists of large graphs are usually encoded to save space and to im- prove decoding speed. Inverted indexes of Information Re- trieval systems keep the lists of postings usually compressed to allow an optimal utilization of memory hierarchy. Sec- ondary indexes of DBMS's are stored similarly to inverted indexes in IR systems. In this paper we propose a novel class of encoders (called VSEncoding from Vector of Splits Encoding) that, roughly speaking, work by partitioning an list of integers into blocks which are efficiently compressed by using simple encoders. Differently from previous work where heuristics were applied during the partitioning step, we carry out this important step via dynamic programming, which leads to produce the optimal solution. Experiments show that our class of encoders outperform all the existing methods in literature by more than 10% (with the exception of Binary Interpolative Coding with which they, roughly, tie) still retaining very fast decompression.Source: ISTI Technical reports, 2010
See at:
ISTI Repository | CNR ExploRA