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Paolo Ciaccia

Università di Bologna, Computer Science and Engineering (DISI), Faculty Member

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Università di Bologna

Csaba Szepesvari

University of Alberta

Chee Wee (Ben) Leong

Educational Testing Service

Sofia University "St. Kliment Ohridski"

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American University in Cairo

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Papers by Paolo Ciaccia

Flexible integration of multimedia sub-queries with qualitative preferences

by Vincent Oria, Ilaria Bartolini, M. Tamer Özsu, and Paolo Ciaccia

Multimedia Tools and Applications, 2007

Complex multimedia queries, aiming to retrieve from large databases those objects that best match... more Complex multimedia queries, aiming to retrieve from large databases those objects that best match the query specification, are usually processed by splitting them into a set of m simpler sub-queries, each dealing with only some of the query features. To determine which are the overall best-matching objects, a rule is then needed to integrate the results of such sub-queries, i.e., how to globally rank the m-dimensional vectors of matching degrees, or partial scores, that objects obtain on the m sub-queries. It is a fact that state-of-the-art approaches all adopt as integration rule a scoring function, such as weighted average, that aggregates the m partial scores into an overall (numerical) similarity score, so that objects can be linearly ordered and only the highest scored ones returned to the user. This choice however forces the system to compromise between the different sub-queries and can easily lead to miss relevant results. In this paper we explore the potentialities of a more general approach, based on the use of qualitative preferences, able to define arbitrary partial (rather than only linear) orders on database objects, so that a larger flexibility is gained in shaping what the user is looking for. For the purpose of efficient evaluation, we propose two integration algorithms able to work with any (monotone) partial order (thus also with scoring functions): MPO, which delivers objects one layer of

Fuzzy Query Languages for Multimedia Data

by Alberto Trombetta and Paolo Ciaccia

… and Management of …, Jan 1, 2001

This chapter presents a fuzzy-based algebra, called SAMEW, to query multimedia objects. SAMEW all... more This chapter presents a fuzzy-based algebra, called SAMEW, to query multimedia objects. SAMEW allows for dealing within a common frameworkwith several aspects relevant to similarity query processing as well as with the inherent imprecision that characterizes data, user requests and query results. Non-Boolean, namely fuzzy and similarity, predicates are used to rank tuples according to specific criteria. Complex multi-predicate queries can be formed by means of logical connectives, whose semantics is parameterized in order to ...

Automatically Joining Pictures to Multiple Taxonomies⋆

by Paolo Ciaccia and I. Bartolini

Automatically providing semantics to multimedia objects is still a major open problem. In this pa... more Automatically providing semantics to multimedia objects is still a major open problem. In this paper we describe recent advances within this context and how they have been implemented within the Scenique image retrieval and browsing system. Scenique is based on a multi-dimensional model, where each dimension is a tree-structured taxonomy of concepts, also called semantic tags, that are used to describe the content of images. We describe an original algorithm that, by exploiting low-level visual features, tags, and metadata associated to an image, is able to predict a high-quality set of semantic tags for that image.

Getting the Best from Uncertain Data

by Paolo Ciaccia and I. Bartolini

PAtterns for Next-generation DAtabase systems: preliminary results of the PANDA project

by Paolo Ciaccia and I. Bartolini

Symposium on Advanced Database Systems, Cetraro, Italy, Mar 1, 2003

Abstract. Nowadays, the vast volume of collected digital data obliges us to employ processing met... more Abstract. Nowadays, the vast volume of collected digital data obliges us to employ processing methods like pattern recognition and data mining in order to reduce the complexity of data management. The output of these techniques are knowledge artifacts, heterogeneous in both structure and semantics. We claim that the concept of pattern is a good candidate for generic representation of these novel information types. The PANDA project is aimed at studying the main issues related to pattern handling. In this paper we ...

Optimal incremental evaluation of preference queries based on ranked sub-queries

by Paolo Ciaccia and I. Bartolini

We consider the problem of efficiently answer preference queries when access to the database is t... more We consider the problem of efficiently answer preference queries when access to the database is through a set of ranked lists and preferences define a strict partial order over the database objects. The iMPO-1 algorithm we introduce minimizes the number of database accesses and can also incrementally return objects as soon as they are guaranteed to be part of the result. As such it generalizes known techniques developed for specific cases, such as Skyline queries.

Relevance Ranking Tuning for Similarity Queries on XML Data

Lecture Notes in Computer Science, 2003

... title>One night only </title> <singer> Elton John </singer> <song>... more ... title>One night only </title> <singer> Elton John </singer> <song> <title> Can you feel the love tonight </title> </song> </cd> </cdstore> <cdstore>Music Store <cd> <title> Chartbusters go pop </title> <singer> <firstname> Elton </firstname> <lastname> John </lastname> </singer ...

A cost model for similarity queries in metric spaces

Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems - PODS '98, 1998

We consider the problem of estimating CPU (distance computations) and I/O costs for processing ra... more We consider the problem of estimating CPU (distance computations) and I/O costs for processing range and k-nearest neighbors queries over metric spaces. Unlike the specific case of vector spaces, where information on data distribution has been exploited to derive cost models for predicting the performance of multi-dimensional access methods, in a generic metric space there is no such a possibility, which makes the problem quite different and requires a novel approach. We insist that the distance distribution of objects can be profitably used to solve the problem, and consequently develop a concrete cost model for the M-tree access method [10]. Our results rely on the assumption that the indexed dataset comes from a metric space which is "homogeneous" enough (in a probabilistic sense) to allow reliable cost estimations even if the distance distribution with respect to a specific query object is unknown. We experimentally validate the model over both real and synthetic datasets, and show how the model can be used to tune the M-tree in order to minimize a combination of CPU and I/O costs. Finally, we sketch how the same approach can be applied to derive a cost model for the vp-tree index structure .

Processing complex similarity queries with distance-based access methods

Lecture Notes in Computer Science, 1998

E cient evaluation of similarity queries is one of the basic requirements for advanced multimedia... more E cient evaluation of similarity queries is one of the basic requirements for advanced multimedia applications. In this paper, we consider the relevant case where complex similarity queries are de ned through a generic language L and whose predicates refer to a single feature F. Contrary to the language level which deals only with similarity scores, the proposed evaluation process is based on distances between feature values -known spatial or metric indexes use distances to evaluate predicates. The proposed solution suggests that the index should process complex queries as a whole, thus evaluating multiple similarity predicates at a time. The exibility of our approach is demonstrated by considering three di erent similarity languages, and showing how the M-tree access method has been extended to this purpose. Experimental results clearly show that performance of the extended M-tree version is consistently better than that of state-of-the-art search algorithms.

Metric information filtering

The traditional problem of similarity search requires to find, within a set of points, those that... more The traditional problem of similarity search requires to find, within a set of points, those that are closer to a query point q, according to a distance function d. In this paper we introduce the novel problem of metric information filtering (MIF): in this scenario, each point x i comes with its own distance function d i and the task is to efficiently determine those points that are close enough, according to d i , to a query point q. MIF can be seen as an extension of both the similarity search problem and of approaches currently used in content-based information filtering, since in MIF user profiles (points) and new items (queries) are compared using arbitrary, personalized, metrics. We introduce the basic concepts of MIF and provide alternative resolution strategies aiming to reduce processing costs. Our experimental results show that the proposed solutions are indeed effective in reducing evaluation costs.

The Many Facets of Approximate Similarity Search

First International Workshop on Similarity Search and Applications (sisap 2008), 2008

In this article, we review the major paradigms for approximate similarity queries and propose a c... more In this article, we review the major paradigms for approximate similarity queries and propose a classification schema that easily allows existing approaches to be compared along several independent coordinates. Then, we discuss the impact that scheduling of index nodes can have on performance and show that, unlike exact similarity queries, no provable optimal scheduling strategy exists for approximate queries. On the positive side, we show that optimalon-the-average schedules are well-defined. We complete by critically reviewing methods for evaluating the quality of approximate results.

Integrating knowledge-based systems and neural networks for navigational tasks

[1991] Proceedings, Advanced Computer Technology, Reliable Systems and Applications, 1991

Project is presented. The project focuses on inherent problems in developing an adaptive system f... more Project is presented. The project focuses on inherent problems in developing an adaptive system for navigational tasks. The proposed architecture is based on both explicif (symbolic) knowledge of the environment and iniplicit knowledge encoded i t the connections of neural networks. The paper overviews the current state of the project, pointing out the most relevant aspects in the functional and structural dcsign of the system. Solutions to specific problems related to short-term goals are also discussed.

Modeling the Propagation of User Preferences

Lecture Notes in Computer Science, 2011

A sound algorithm for region-based image retrieval using an index

by Paolo Ciaccia and Ilaria Bartolini

Proceedings 11th International Workshop on Database and Expert Systems Applications, 2000

Region-based image retrieval systems aim to improve the effectiveness of content-based search by ... more Region-based image retrieval systems aim to improve the effectiveness of content-based search by decomposing each image into a set of "homogeneous" regions. Thus, similarity between images is assessed by computing similarity between pairs of regions and then combining the results at the image level. In this paper we propose the first provably sound algorithm for performing region-based similarity search when regions are accessed through an index. Experimental results demonstrate the effectiveness of our approach, as also compared to alternative retrieval strategies.

Principles of Information Filtering in Metric Spaces

2009 Second International Workshop on Similarity Search and Applications, 2009

The traditional problem of similarity search requires to find, within a set of points, those that... more The traditional problem of similarity search requires to find, within a set of points, those that are closer to a query point q, according to a distance function d. In this paper we introduce the novel problem of metric filtering: in this scenario, each data point xi possesses its own distance function di and the task is to find those points that are close enough, according to di, to a query point q. This minor difference in the problem formulation introduces a series of challenges from the point of view of efficient evaluation. We provide basic definitions and alternative pivot-based resolution strategies, presenting results from a preliminary experimentation that show how the proposed solutions are indeed effective in reducing evaluation costs.

Dietz, HG, see Kang, MH

by Paolo Ciaccia and dario maio

Fuzzy query languages for multimedia data, Design and management of multimedia information systems: opportunities and challenges

Basi di conoscenza e basi di dati: memorizzazione degli aspetti estensionali

by sonia bergamaschi and Paolo Ciaccia

WISDOM: Ricerca Intelligente su Web basata su Ontologie di Dominio

by Paolo Ciaccia and sonia bergamaschi

Lezioni di basi di dati

Flexible integration of multimedia sub-queries with qualitative preferences

by Vincent Oria, Ilaria Bartolini, M. Tamer Özsu, and Paolo Ciaccia

Multimedia Tools and Applications, 2007

Complex multimedia queries, aiming to retrieve from large databases those objects that best match... more Complex multimedia queries, aiming to retrieve from large databases those objects that best match the query specification, are usually processed by splitting them into a set of m simpler sub-queries, each dealing with only some of the query features. To determine which are the overall best-matching objects, a rule is then needed to integrate the results of such sub-queries, i.e., how to globally rank the m-dimensional vectors of matching degrees, or partial scores, that objects obtain on the m sub-queries. It is a fact that state-of-the-art approaches all adopt as integration rule a scoring function, such as weighted average, that aggregates the m partial scores into an overall (numerical) similarity score, so that objects can be linearly ordered and only the highest scored ones returned to the user. This choice however forces the system to compromise between the different sub-queries and can easily lead to miss relevant results. In this paper we explore the potentialities of a more general approach, based on the use of qualitative preferences, able to define arbitrary partial (rather than only linear) orders on database objects, so that a larger flexibility is gained in shaping what the user is looking for. For the purpose of efficient evaluation, we propose two integration algorithms able to work with any (monotone) partial order (thus also with scoring functions): MPO, which delivers objects one layer of

Fuzzy Query Languages for Multimedia Data

by Alberto Trombetta and Paolo Ciaccia

… and Management of …, Jan 1, 2001

This chapter presents a fuzzy-based algebra, called SAMEW, to query multimedia objects. SAMEW all... more This chapter presents a fuzzy-based algebra, called SAMEW, to query multimedia objects. SAMEW allows for dealing within a common frameworkwith several aspects relevant to similarity query processing as well as with the inherent imprecision that characterizes data, user requests and query results. Non-Boolean, namely fuzzy and similarity, predicates are used to rank tuples according to specific criteria. Complex multi-predicate queries can be formed by means of logical connectives, whose semantics is parameterized in order to ...

Automatically Joining Pictures to Multiple Taxonomies⋆

by Paolo Ciaccia and I. Bartolini

Automatically providing semantics to multimedia objects is still a major open problem. In this pa... more Automatically providing semantics to multimedia objects is still a major open problem. In this paper we describe recent advances within this context and how they have been implemented within the Scenique image retrieval and browsing system. Scenique is based on a multi-dimensional model, where each dimension is a tree-structured taxonomy of concepts, also called semantic tags, that are used to describe the content of images. We describe an original algorithm that, by exploiting low-level visual features, tags, and metadata associated to an image, is able to predict a high-quality set of semantic tags for that image.

Getting the Best from Uncertain Data

by Paolo Ciaccia and I. Bartolini

PAtterns for Next-generation DAtabase systems: preliminary results of the PANDA project

by Paolo Ciaccia and I. Bartolini

Symposium on Advanced Database Systems, Cetraro, Italy, Mar 1, 2003

Abstract. Nowadays, the vast volume of collected digital data obliges us to employ processing met... more Abstract. Nowadays, the vast volume of collected digital data obliges us to employ processing methods like pattern recognition and data mining in order to reduce the complexity of data management. The output of these techniques are knowledge artifacts, heterogeneous in both structure and semantics. We claim that the concept of pattern is a good candidate for generic representation of these novel information types. The PANDA project is aimed at studying the main issues related to pattern handling. In this paper we ...

Optimal incremental evaluation of preference queries based on ranked sub-queries

by Paolo Ciaccia and I. Bartolini

We consider the problem of efficiently answer preference queries when access to the database is t... more We consider the problem of efficiently answer preference queries when access to the database is through a set of ranked lists and preferences define a strict partial order over the database objects. The iMPO-1 algorithm we introduce minimizes the number of database accesses and can also incrementally return objects as soon as they are guaranteed to be part of the result. As such it generalizes known techniques developed for specific cases, such as Skyline queries.

Relevance Ranking Tuning for Similarity Queries on XML Data

Lecture Notes in Computer Science, 2003

... title>One night only </title> <singer> Elton John </singer> <song>... more ... title>One night only </title> <singer> Elton John </singer> <song> <title> Can you feel the love tonight </title> </song> </cd> </cdstore> <cdstore>Music Store <cd> <title> Chartbusters go pop </title> <singer> <firstname> Elton </firstname> <lastname> John </lastname> </singer ...

A cost model for similarity queries in metric spaces

Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems - PODS '98, 1998

We consider the problem of estimating CPU (distance computations) and I/O costs for processing ra... more We consider the problem of estimating CPU (distance computations) and I/O costs for processing range and k-nearest neighbors queries over metric spaces. Unlike the specific case of vector spaces, where information on data distribution has been exploited to derive cost models for predicting the performance of multi-dimensional access methods, in a generic metric space there is no such a possibility, which makes the problem quite different and requires a novel approach. We insist that the distance distribution of objects can be profitably used to solve the problem, and consequently develop a concrete cost model for the M-tree access method [10]. Our results rely on the assumption that the indexed dataset comes from a metric space which is "homogeneous" enough (in a probabilistic sense) to allow reliable cost estimations even if the distance distribution with respect to a specific query object is unknown. We experimentally validate the model over both real and synthetic datasets, and show how the model can be used to tune the M-tree in order to minimize a combination of CPU and I/O costs. Finally, we sketch how the same approach can be applied to derive a cost model for the vp-tree index structure .

Processing complex similarity queries with distance-based access methods

Lecture Notes in Computer Science, 1998

E cient evaluation of similarity queries is one of the basic requirements for advanced multimedia... more E cient evaluation of similarity queries is one of the basic requirements for advanced multimedia applications. In this paper, we consider the relevant case where complex similarity queries are de ned through a generic language L and whose predicates refer to a single feature F. Contrary to the language level which deals only with similarity scores, the proposed evaluation process is based on distances between feature values -known spatial or metric indexes use distances to evaluate predicates. The proposed solution suggests that the index should process complex queries as a whole, thus evaluating multiple similarity predicates at a time. The exibility of our approach is demonstrated by considering three di erent similarity languages, and showing how the M-tree access method has been extended to this purpose. Experimental results clearly show that performance of the extended M-tree version is consistently better than that of state-of-the-art search algorithms.

Metric information filtering

The traditional problem of similarity search requires to find, within a set of points, those that... more The traditional problem of similarity search requires to find, within a set of points, those that are closer to a query point q, according to a distance function d. In this paper we introduce the novel problem of metric information filtering (MIF): in this scenario, each point x i comes with its own distance function d i and the task is to efficiently determine those points that are close enough, according to d i , to a query point q. MIF can be seen as an extension of both the similarity search problem and of approaches currently used in content-based information filtering, since in MIF user profiles (points) and new items (queries) are compared using arbitrary, personalized, metrics. We introduce the basic concepts of MIF and provide alternative resolution strategies aiming to reduce processing costs. Our experimental results show that the proposed solutions are indeed effective in reducing evaluation costs.

The Many Facets of Approximate Similarity Search

First International Workshop on Similarity Search and Applications (sisap 2008), 2008

In this article, we review the major paradigms for approximate similarity queries and propose a c... more In this article, we review the major paradigms for approximate similarity queries and propose a classification schema that easily allows existing approaches to be compared along several independent coordinates. Then, we discuss the impact that scheduling of index nodes can have on performance and show that, unlike exact similarity queries, no provable optimal scheduling strategy exists for approximate queries. On the positive side, we show that optimalon-the-average schedules are well-defined. We complete by critically reviewing methods for evaluating the quality of approximate results.

Integrating knowledge-based systems and neural networks for navigational tasks

[1991] Proceedings, Advanced Computer Technology, Reliable Systems and Applications, 1991

Project is presented. The project focuses on inherent problems in developing an adaptive system f... more Project is presented. The project focuses on inherent problems in developing an adaptive system for navigational tasks. The proposed architecture is based on both explicif (symbolic) knowledge of the environment and iniplicit knowledge encoded i t the connections of neural networks. The paper overviews the current state of the project, pointing out the most relevant aspects in the functional and structural dcsign of the system. Solutions to specific problems related to short-term goals are also discussed.

Modeling the Propagation of User Preferences

Lecture Notes in Computer Science, 2011

A sound algorithm for region-based image retrieval using an index

by Paolo Ciaccia and Ilaria Bartolini

Proceedings 11th International Workshop on Database and Expert Systems Applications, 2000

Region-based image retrieval systems aim to improve the effectiveness of content-based search by ... more Region-based image retrieval systems aim to improve the effectiveness of content-based search by decomposing each image into a set of "homogeneous" regions. Thus, similarity between images is assessed by computing similarity between pairs of regions and then combining the results at the image level. In this paper we propose the first provably sound algorithm for performing region-based similarity search when regions are accessed through an index. Experimental results demonstrate the effectiveness of our approach, as also compared to alternative retrieval strategies.

Principles of Information Filtering in Metric Spaces

2009 Second International Workshop on Similarity Search and Applications, 2009

The traditional problem of similarity search requires to find, within a set of points, those that... more The traditional problem of similarity search requires to find, within a set of points, those that are closer to a query point q, according to a distance function d. In this paper we introduce the novel problem of metric filtering: in this scenario, each data point xi possesses its own distance function di and the task is to find those points that are close enough, according to di, to a query point q. This minor difference in the problem formulation introduces a series of challenges from the point of view of efficient evaluation. We provide basic definitions and alternative pivot-based resolution strategies, presenting results from a preliminary experimentation that show how the proposed solutions are indeed effective in reducing evaluation costs.

Dietz, HG, see Kang, MH

by Paolo Ciaccia and dario maio

Fuzzy query languages for multimedia data, Design and management of multimedia information systems: opportunities and challenges

Basi di conoscenza e basi di dati: memorizzazione degli aspetti estensionali

by sonia bergamaschi and Paolo Ciaccia

WISDOM: Ricerca Intelligente su Web basata su Ontologie di Dominio

by Paolo Ciaccia and sonia bergamaschi

Lezioni di basi di dati