2011
Conference article
Restricted
Fuzzy ontologies and fuzzy integrals
Bobillo F, Straccia U
Fuzzy ontologies extend classical ontologies to allow the representation of imprecise and vague knowledge. Although a relatively important amount of work has been carried out in the last years and they have been successfully used in several applications, several notions from fuzzy logic, such as fuzzy integrals, have not been considered yet in fuzzy ontologies. In this work, we show how to support fuzzy integrals in fuzzy ontologies. As a theoretical formalism, we provide the syntax and semantics of a fuzzy Description Logic with fuzzy integrals. We also provide a reasoning algorithm for a family of fuzzy integrals and show how to encode them into the language Fuzzy OWL 2.DOI: 10.1109/isda.2011.6121841
Metrics:
Bobillo F, Straccia U
Fuzzy ontologies extend classical ontologies to allow the representation of imprecise and vague knowledge. Although a relatively important amount of work has been carried out in the last years and they have been successfully used in several applications, several notions from fuzzy logic, such as fuzzy integrals, have not been considered yet in fuzzy ontologies. In this work, we show how to support fuzzy integrals in fuzzy ontologies. As a theoretical formalism, we provide the syntax and semantics of a fuzzy Description Logic with fuzzy integrals. We also provide a reasoning algorithm for a family of fuzzy integrals and show how to encode them into the language Fuzzy OWL 2.DOI: 10.1109/isda.2011.6121841
Metrics:
2004
Conference article
Open Access
Transforming fuzzy description logics into classical description logics
Straccia U
In this paper we consider Description Logics (DLs), which are logics for managing structured knowledge, with a well-known fuzzy extension to deal with vague information. While for fuzzy DLs ad-hoc, tableaux-like reasoning procedures have been given in the literature, the topic of this paper is to present a reasoning preserving transformation of fuzzy DLs into classical DLs. This has the considerable practical consequence that reasoning in fuzzy DLs is feasible using already existing DL systems.DOI: 10.1007/978-3-540-30227-8_33
Metrics:
Straccia U
In this paper we consider Description Logics (DLs), which are logics for managing structured knowledge, with a well-known fuzzy extension to deal with vague information. While for fuzzy DLs ad-hoc, tableaux-like reasoning procedures have been given in the literature, the topic of this paper is to present a reasoning preserving transformation of fuzzy DLs into classical DLs. This has the considerable practical consequence that reasoning in fuzzy DLs is feasible using already existing DL systems.DOI: 10.1007/978-3-540-30227-8_33
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| doi.org 
| CNR IRIS | CNR IRIS | link.springer.com | www.scopus.com
2005
Conference article
Restricted
sPLMap: A probabilistic approach to schema matching
Nottelmann H, Straccia U
This paper introduces the first formal framework for learning mappings between heterogeneous schemas, which is based on probabilistic logics. This task, also called ``schema matching'', is a crucial step in integrating heterogeneous collections. As schemas may have different granularities, and as schema attributes do not always match precisely, a general-purpose schema mapping approach requires support for uncertain mappings, and mappings have to be learned automatically. The framework combines different classifiers for finding suitable mapping candidates (together with their weights), and selects that set of mapping rules which is the most likely one. Finally, the framework with different variants has been evaluated on two different data sets.DOI: 10.1007/978-3-540-31865-1_7
Metrics:
Nottelmann H, Straccia U
This paper introduces the first formal framework for learning mappings between heterogeneous schemas, which is based on probabilistic logics. This task, also called ``schema matching'', is a crucial step in integrating heterogeneous collections. As schemas may have different granularities, and as schema attributes do not always match precisely, a general-purpose schema mapping approach requires support for uncertain mappings, and mappings have to be learned automatically. The framework combines different classifiers for finding suitable mapping candidates (together with their weights), and selects that set of mapping rules which is the most likely one. Finally, the framework with different variants has been evaluated on two different data sets.DOI: 10.1007/978-3-540-31865-1_7
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See at:
doi.org | CNR IRIS | CNR IRIS | link.springer.com | www.scopus.com
2005
Journal article
Restricted
Any-world assumptions in logic programming
Loyer Y, Straccia U
Due to the usual incompleteness of information representation, any approach to assign a semantics to logic programs has to rely on a default assumption on the missing information. The emph{stable model semantics}, that has become the dominating approach to give semantics to logic programs, relies on the Closed World Assumption (CWA), which asserts that by default the truth of an atom is emph{false}. There is a second well-known assumption, called emph{Open World Assumption} (OWA), which asserts that the truth of the atoms is supposed to be emph{unknown} by default. However, the CWA, the OWA and the combination of them are extremal, though important, assumptions over a large variety of possible assumptions on the truth of the atoms, whenever the truth is taken from emph{an arbitrary truth space}. The topic of this paper is to allow emph{any} assignment (ie interpretation), over a truth space, to be a default assumption. Our main result is that our extension is conservative in the sense that under the ``everywhere false' default assumption (CWA) the usual stable model semantics is captured. Due to the generality and the purely algebraic nature of our approach, it abstracts from the particular formalism of choice and the results may be applied in other contexts as well.Source: THEORETICAL COMPUTER SCIENCE, vol. 342, pp. 351-381
Loyer Y, Straccia U
Due to the usual incompleteness of information representation, any approach to assign a semantics to logic programs has to rely on a default assumption on the missing information. The emph{stable model semantics}, that has become the dominating approach to give semantics to logic programs, relies on the Closed World Assumption (CWA), which asserts that by default the truth of an atom is emph{false}. There is a second well-known assumption, called emph{Open World Assumption} (OWA), which asserts that the truth of the atoms is supposed to be emph{unknown} by default. However, the CWA, the OWA and the combination of them are extremal, though important, assumptions over a large variety of possible assumptions on the truth of the atoms, whenever the truth is taken from emph{an arbitrary truth space}. The topic of this paper is to allow emph{any} assignment (ie interpretation), over a truth space, to be a default assumption. Our main result is that our extension is conservative in the sense that under the ``everywhere false' default assumption (CWA) the usual stable model semantics is captured. Due to the generality and the purely algebraic nature of our approach, it abstracts from the particular formalism of choice and the results may be applied in other contexts as well.Source: THEORETICAL COMPUTER SCIENCE, vol. 342, pp. 351-381
2005
Conference article
Restricted
Query answering in normal logic programs under uncertainty
Straccia U
We present a simple, yet general top-down query answering procedure for normal logic programs over lattices and bilattices, where functions may appear in the rule bodies. Its interest relies on the fact that many approaches to paraconsistency and uncertainty in logic programs with or without non-monotonic negation are based on bilattices or lattices, respectively.DOI: 10.1007/11518655_58
Metrics:
Straccia U
We present a simple, yet general top-down query answering procedure for normal logic programs over lattices and bilattices, where functions may appear in the rule bodies. Its interest relies on the fact that many approaches to paraconsistency and uncertainty in logic programs with or without non-monotonic negation are based on bilattices or lattices, respectively.DOI: 10.1007/11518655_58
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doi.org | CNR IRIS | CNR IRIS | link.springer.com
2005
Conference article
Open Access
Towards a fuzzy description logic for the semantic Web (preliminary report)
Straccia U
In this paper we present a fuzzy version of ${cal SHOIN}(D)$, the corresponding Description Logic of the ontology description language OWL DL. We show that the representation and reasoning capabilities of fuzzy SHOIN(D) go clearly beyond classical SHOIN(D). We present its syntax and semantics. Interesting features are that concrete domains are fuzzy and entailment and subsumption relationships may hold to some degree in the unit interval [0,1].DOI: 10.1007/11431053_12
Metrics:
Straccia U
In this paper we present a fuzzy version of ${cal SHOIN}(D)$, the corresponding Description Logic of the ontology description language OWL DL. We show that the representation and reasoning capabilities of fuzzy SHOIN(D) go clearly beyond classical SHOIN(D). We present its syntax and semantics. Interesting features are that concrete domains are fuzzy and entailment and subsumption relationships may hold to some degree in the unit interval [0,1].DOI: 10.1007/11431053_12
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link.springer.com | doi.org | CNR IRIS | CNR IRIS | link.springer.com | www.scopus.com
2005
Conference article
Open Access
Uncertainty management in logic programming: simple and effective top-down query answering
Straccia U
We present a simple, yet general top-down query answering procedure for logic programs managing uncertainty. The main features are: ii{i} the certainty values are taken from a certainty lattice; ii{ii} computable functions may appear in the rule bodies to manipulate certainties; and ii{iii} we solve the problem by a reduction to an equational systems, for which we device a top-down procedure.DOI: 10.1007/11552451_103
Metrics:
Straccia U
We present a simple, yet general top-down query answering procedure for logic programs managing uncertainty. The main features are: ii{i} the certainty values are taken from a certainty lattice; ii{ii} computable functions may appear in the rule bodies to manipulate certainties; and ii{iii} we solve the problem by a reduction to an equational systems, for which we device a top-down procedure.DOI: 10.1007/11552451_103
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faure.isti.cnr.it | doi.org | CNR IRIS | CNR IRIS | link.springer.com
2005
Conference article
Restricted
oMAP: combining classifiers for aligning automatically OWL ontologies
Sraccia U., Troncy R.
This paper introduces a method and a tool for automatically aligning OWL ontologies, a crucial step for achieving the interoperability of heterogeneous systems in the Semantic Web. Different components are combined for finding suitable mapping candidates (together with their weights), and the set of rules with maximum matching probability is selected. Machine learning-based classifiers and a new classifier using the structure and the semantics of the OWL ontologies are proposed. Our method has been implemented and evaluated on an independent test set provided by an international ontology alignment contest. We provide the results of this evaluation with respect to the other competitors.Source: 6th International Conference on Web Information Systems Engineering, pp. 133–147, New York, Novembre 2005
DOI: 10.1007/11581062_11
Metrics:
Sraccia U., Troncy R.
This paper introduces a method and a tool for automatically aligning OWL ontologies, a crucial step for achieving the interoperability of heterogeneous systems in the Semantic Web. Different components are combined for finding suitable mapping candidates (together with their weights), and the set of rules with maximum matching probability is selected. Machine learning-based classifiers and a new classifier using the structure and the semantics of the OWL ontologies are proposed. Our method has been implemented and evaluated on an independent test set provided by an international ontology alignment contest. We provide the results of this evaluation with respect to the other competitors.Source: 6th International Conference on Web Information Systems Engineering, pp. 133–147, New York, Novembre 2005
DOI: 10.1007/11581062_11
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See at:
doi.org | link.springer.com | CNR ExploRA
2006
Journal article
Restricted
Description logics over lattices
Straccia U
It is generally accepted that knowledge based systems would be smarter if they could manage uncertainty and/or imprecision. In this paper we extend Description Logics, well-known logics for managing structured knowledge, allowing to express that a sentence is not just true or false, but true to some degree, which is taken from a certainty lattice.Source: INTERNATIONAL JOURNAL OF UNCERTAINTY, FUZZINESS AND KNOWLEDGE BASED SYSTEMS, vol. 14 (issue 1), pp. 1-16
DOI: 10.1142/s0218488506003807
Metrics:
Straccia U
It is generally accepted that knowledge based systems would be smarter if they could manage uncertainty and/or imprecision. In this paper we extend Description Logics, well-known logics for managing structured knowledge, allowing to express that a sentence is not just true or false, but true to some degree, which is taken from a certainty lattice.Source: INTERNATIONAL JOURNAL OF UNCERTAINTY, FUZZINESS AND KNOWLEDGE BASED SYSTEMS, vol. 14 (issue 1), pp. 1-16
DOI: 10.1142/s0218488506003807
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International Journal of Uncertainty Fuzziness and Knowledge-Based Systems | CNR IRIS | CNR IRIS | www.worldscientific.com
2006
Conference article
Open Access
Towards distributed information retrieval in the semantic Web: query reformulation using the oMAP framework
Straccia U, Troncy R
This paper introduces a general methodology for performing distributed search in the Semantic Web. We propose to define this task as a three steps process, namely resource selection, query reformulation/ontology alignment and rank aggregation/data fusion. For the second problem, we have implemented oMAP, a formal framework for automatically aligning OWL ontologies. In oMAP, different components are combined for finding suitable mapping candidates (together with their weights), and the set of rules with maximum matching probability is selected. Among these components, traditional terminological-based classifiers, machine learning-based classifiers and a new classifier using the structure and the semantics of the OWL ontologies are proposed. oMAP has been evaluated on international test sets.DOI: 10.1007/11762256_29
Metrics:
Straccia U, Troncy R
This paper introduces a general methodology for performing distributed search in the Semantic Web. We propose to define this task as a three steps process, namely resource selection, query reformulation/ontology alignment and rank aggregation/data fusion. For the second problem, we have implemented oMAP, a formal framework for automatically aligning OWL ontologies. In oMAP, different components are combined for finding suitable mapping candidates (together with their weights), and the set of rules with maximum matching probability is selected. Among these components, traditional terminological-based classifiers, machine learning-based classifiers and a new classifier using the structure and the semantics of the OWL ontologies are proposed. oMAP has been evaluated on international test sets.DOI: 10.1007/11762256_29
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NARCIS | link.springer.com | doi.org | CNR IRIS | CNR IRIS | link.springer.com
2001
Journal article
Open Access
Reasoning within fuzzy description logics
Straccia U
Description Logics (DLs) are suitable, well-known, logics for managing structured knowledge. They allow reasoning about individuals and well defined concepts, i.e., set of individuals with common properties. The experience in using DLs in applications has shown that in many cases we would like to extend their capabilities. In particular, their use in the context of Multimedia Information Retrieval (MIR) leads to the convincement that such DLs should allow the treatment of the inherent imprecision in multimedia object content representation and retrieval. In this paper we will present a fuzzy extension of ALC, combining Zadeh's fuzzy logic with a classical DL. In particular, concepts becomes fuzzy and, thus, reasoning about imprecise concepts is supported. We will define its syntax, its semantics, describe its properties and present a constraint propagation calculus for reasoning in it.Source: THE JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, vol. 14, pp. 137-166
DOI: 10.1613/jair.813
DOI: 10.48550/arxiv.1106.0667
Metrics:
Straccia U
Description Logics (DLs) are suitable, well-known, logics for managing structured knowledge. They allow reasoning about individuals and well defined concepts, i.e., set of individuals with common properties. The experience in using DLs in applications has shown that in many cases we would like to extend their capabilities. In particular, their use in the context of Multimedia Information Retrieval (MIR) leads to the convincement that such DLs should allow the treatment of the inherent imprecision in multimedia object content representation and retrieval. In this paper we will present a fuzzy extension of ALC, combining Zadeh's fuzzy logic with a classical DL. In particular, concepts becomes fuzzy and, thus, reasoning about imprecise concepts is supported. We will define its syntax, its semantics, describe its properties and present a constraint propagation calculus for reasoning in it.Source: THE JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, vol. 14, pp. 137-166
DOI: 10.1613/jair.813
DOI: 10.48550/arxiv.1106.0667
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arXiv.org e-Print Archive | The Journal of Artificial Intelligence Research | The Journal of Artificial Intelligence Research | doi.org | CNR IRIS | CNR IRIS | jair.org | www.scopus.com
2007
Conference article
Restricted
A top-down query answering procedure for normal logic programs under the any-world assumption
Straccia U
The Any-World Assumption (AWA) has been introduced for normal logic programs as a generalization of the well-known notions of Closed World Assumption (CWA) and the Open World Assumption (OWA). The AWA allows any assignment (i.e., interpretation), over a truth space (bilattice), to be a default assumption and, thus, the CWA and OWA are just special cases. To answer queries, we provide a novel and simple top-down procedure.DOI: 10.1007/978-3-540-75256-1
Metrics:
Straccia U
The Any-World Assumption (AWA) has been introduced for normal logic programs as a generalization of the well-known notions of Closed World Assumption (CWA) and the Open World Assumption (OWA). The AWA allows any assignment (i.e., interpretation), over a truth space (bilattice), to be a default assumption and, thus, the CWA and OWA are just special cases. To answer queries, we provide a novel and simple top-down procedure.DOI: 10.1007/978-3-540-75256-1
Metrics:
See at:
doi.org | CNR IRIS | CNR IRIS | link.springer.com
2007
Conference article
Open Access
Description logic programs under probabilistic uncertainty and fuzzy vagueness
Lukasiewicz T, Straccia U
This paper is directed towards an infrastructure for handling both uncertainty and vagueness in the Rules, Logic, and Proof layers of the Semantic Web. More concretely, we present probabilistic fuzzy description logic programs, which combine fuzzy description logics, fuzzy logic programs (with stratified nonmonotonic negation), and probabilistic uncertainty in a uniform framework for the Semantic Web. We define important concepts dealing with both probabilistic uncertainty and fuzzy vagueness, such as the expected truth value of a crisp sentence and the probability of a vague sentence. Furthermore, we describe a shopping agent example, which gives evidence of the usefulness of probabilistic fuzzy~description logic programs in realistic web applications. In the extended~report, we also provide algorithms for query processing in probabilistic fuzzy description logic programs, and we delineate a special case where query processing~can be done in polynomial time in the data complexity.DOI: 10.1007/978-3-540-75256-1_19
DOI: 10.1016/j.ijar.2009.03.004
Metrics:
Lukasiewicz T, Straccia U
This paper is directed towards an infrastructure for handling both uncertainty and vagueness in the Rules, Logic, and Proof layers of the Semantic Web. More concretely, we present probabilistic fuzzy description logic programs, which combine fuzzy description logics, fuzzy logic programs (with stratified nonmonotonic negation), and probabilistic uncertainty in a uniform framework for the Semantic Web. We define important concepts dealing with both probabilistic uncertainty and fuzzy vagueness, such as the expected truth value of a crisp sentence and the probability of a vague sentence. Furthermore, we describe a shopping agent example, which gives evidence of the usefulness of probabilistic fuzzy~description logic programs in realistic web applications. In the extended~report, we also provide algorithms for query processing in probabilistic fuzzy description logic programs, and we delineate a special case where query processing~can be done in polynomial time in the data complexity.DOI: 10.1007/978-3-540-75256-1_19
DOI: 10.1016/j.ijar.2009.03.004
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International Journal of Approximate Reasoning | Oxford University Research Archive | Oxford University Research Archive | Oxford University Research Archive | ora.ox.ac.uk | doi.org | CNR IRIS | CNR IRIS | link.springer.com | Oxford University Research Archive | Oxford University Research Archive | www.scopus.com
2007
Journal article
Open Access
Information retrieval and machine learning for probabilistic schema matching
Nottelmann H, Straccia U
Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain, or for distributed IR in federated digital libraries. This paper introduces a probabilistic framework, called sPLMap, for automatically learning schema mapping rules, based on given instances of both schemas. Different techniques, mostly from the IR and machine learning fields, are combined for finding suitable mapping candidates. Our approach gives a probabilistic interpretation of the prediction weights of the candidates, selects the rule set with highest matching probability, and outputs probabilistic rules which are capable to deal with the intrinsic uncertainty of the mapping process. Our approach with different variants has been evaluated on several test sets.Source: INFORMATION PROCESSING & MANAGEMENT, vol. 43 (issue 3), pp. 552-576
DOI: 10.1016/j.ipm.2006.10.014
DOI: 10.1145/1099554.1099634
Metrics:
Nottelmann H, Straccia U
Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain, or for distributed IR in federated digital libraries. This paper introduces a probabilistic framework, called sPLMap, for automatically learning schema mapping rules, based on given instances of both schemas. Different techniques, mostly from the IR and machine learning fields, are combined for finding suitable mapping candidates. Our approach gives a probabilistic interpretation of the prediction weights of the candidates, selects the rule set with highest matching probability, and outputs probabilistic rules which are capable to deal with the intrinsic uncertainty of the mapping process. Our approach with different variants has been evaluated on several test sets.Source: INFORMATION PROCESSING & MANAGEMENT, vol. 43 (issue 3), pp. 552-576
DOI: 10.1016/j.ipm.2006.10.014
DOI: 10.1145/1099554.1099634
Metrics:
See at:
Information Processing & Management | Information Processing & Management | doi.org | CNR IRIS | CNR IRIS | www.sciencedirect.com
2007
Conference article
Open Access
Tightly integrated fuzzy description logic programs under the answer semantics for the semantic Web
Lukasiewicz T, Straccia U
We present a novel approach to fuzzy dl-programs under the answer set semantics, which is a tight integration of fuzzy disjunctive programs under the answer set semantics with fuzzy description logics. From a different perspective, it is a generalization of tightly integrated disjunctive dl-programs by fuzzy vagueness in both the description logic and the logic program component. We show that the new formalism faithfully extends both fuzzy disjunctive programs and fuzzy description logics, and that under suitable assumptions, reasoning in the new formalism is decidable. Furthermore, we present a polynomial reduction of certain fuzzy dl-programs to tightly integrated disjunctive dl-programs. We also provide a special case of fuzzy dl-programs for which deciding consistency and~query processing have both a polynomial data complexity.DOI: 10.1007/978-3-540-72982-2_23
Metrics:
Lukasiewicz T, Straccia U
We present a novel approach to fuzzy dl-programs under the answer set semantics, which is a tight integration of fuzzy disjunctive programs under the answer set semantics with fuzzy description logics. From a different perspective, it is a generalization of tightly integrated disjunctive dl-programs by fuzzy vagueness in both the description logic and the logic program component. We show that the new formalism faithfully extends both fuzzy disjunctive programs and fuzzy description logics, and that under suitable assumptions, reasoning in the new formalism is decidable. Furthermore, we present a polynomial reduction of certain fuzzy dl-programs to tightly integrated disjunctive dl-programs. We also provide a special case of fuzzy dl-programs for which deciding consistency and~query processing have both a polynomial data complexity.DOI: 10.1007/978-3-540-72982-2_23
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Oxford University Research Archive | www.kr.tuwien.ac.at | doi.org | CNR IRIS | CNR IRIS | link.springer.com | Oxford University Research Archive | www.scopus.com
2007
Conference article
Open Access
Top-K retrieval in description logic programs under vagueness for the semantic Web
Lukasiewicz T, Straccia U
Description Logics (DLs) and Logic Programs (LPs) are important representation languages for the Semantic Web. In this paper, we address an emerging problem in such languages, namely the problem of evaluating ranked top-k queries. Specifically, we show how to compute the top-k answers in a data complexity tractable combination of DLs and LPs.DOI: 10.1007/978-3-540-75410-7_2
Metrics:
Lukasiewicz T, Straccia U
Description Logics (DLs) and Logic Programs (LPs) are important representation languages for the Semantic Web. In this paper, we address an emerging problem in such languages, namely the problem of evaluating ranked top-k queries. Specifically, we show how to compute the top-k answers in a data complexity tractable combination of DLs and LPs.DOI: 10.1007/978-3-540-75410-7_2
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faure.isti.cnr.it | doi.org | CNR IRIS | CNR IRIS | link.springer.com
2007
Conference article
Open Access
Vague knowledge bases for matchmaking in P2P E-Marketplaces
Ragone A, Straccia U, Di Noia T, Di Sciascio E, Donini F M
In this paper we propose an approach to semantic matchmaking that exploits various knowledge representation technologies to find most promising partners in peer-to-peer e-marketplaces. In particular we mix in a formal and principled way the semantic expressiveness of DLR-lite Logic Programs, fuzzy logic and utility theory. We adopt DLR-Lite Logic Programs to obtain a reasonable compromise between expressiveness and complexity to ensure the scalability of our approach to large e-marketplaces, and Fuzzy Logic to model logical specifications as soft constraints. Furthermore, fully exploiting the peer-to-peer paradigm, we consider in the matchmaking process preferences and corresponding utilities of both parties.DOI: 10.1007/978-3-540-72667-8_30
Metrics:
Ragone A, Straccia U, Di Noia T, Di Sciascio E, Donini F M
In this paper we propose an approach to semantic matchmaking that exploits various knowledge representation technologies to find most promising partners in peer-to-peer e-marketplaces. In particular we mix in a formal and principled way the semantic expressiveness of DLR-lite Logic Programs, fuzzy logic and utility theory. We adopt DLR-Lite Logic Programs to obtain a reasonable compromise between expressiveness and complexity to ensure the scalability of our approach to large e-marketplaces, and Fuzzy Logic to model logical specifications as soft constraints. Furthermore, fully exploiting the peer-to-peer paradigm, we consider in the matchmaking process preferences and corresponding utilities of both parties.DOI: 10.1007/978-3-540-72667-8_30
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link.springer.com | doi.org | CNR IRIS | CNR IRIS | link.springer.com | www.scopus.com
2003
Conference article
Open Access
The Approximate Well-founded Semantics for Logic Programs with Uncertainty
Loyer Y, Straccia U
The management of uncertain information in logic programs becomes to be important whenever the real world information to be represented is of imperfect nature and the classical crisp {em true, false} approximation is not adequate. A general framework, called emph{Parametric Deductive Databases with Uncertainty} (PDDU) framework~cite{Lakshmanan01}, was proposed as a unifying umbrella for many existing approaches towards the manipulation of uncertainty in logic programs. We extend PDDU with (non-monotonic) negation, a well-known and important feature of logic programs. We show that, dealing with uncertain and incomplete knowledge, atoms should be assigned only approximations of uncertainty values, unless some assumption is used to complete the knowledge. We rely on the closed world assumption to infer as much default ``false'' knowledge as possible. Our approach leads also to a novel characterizations, both epistemic and operational, of the well-founded semantics in PDDU, and preserves the continuity of the immediate consequence operator, a major feature of the classical PDDU framework.DOI: 10.1007/978-3-540-45138-9_48
Metrics:
Loyer Y, Straccia U
The management of uncertain information in logic programs becomes to be important whenever the real world information to be represented is of imperfect nature and the classical crisp {em true, false} approximation is not adequate. A general framework, called emph{Parametric Deductive Databases with Uncertainty} (PDDU) framework~cite{Lakshmanan01}, was proposed as a unifying umbrella for many existing approaches towards the manipulation of uncertainty in logic programs. We extend PDDU with (non-monotonic) negation, a well-known and important feature of logic programs. We show that, dealing with uncertain and incomplete knowledge, atoms should be assigned only approximations of uncertainty values, unless some assumption is used to complete the knowledge. We rely on the closed world assumption to infer as much default ``false'' knowledge as possible. Our approach leads also to a novel characterizations, both epistemic and operational, of the well-founded semantics in PDDU, and preserves the continuity of the immediate consequence operator, a major feature of the classical PDDU framework.DOI: 10.1007/978-3-540-45138-9_48
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faure.isti.cnr.it | doi.org | CNR IRIS | CNR IRIS | link.springer.com
2003
Conference article
Open Access
Default Knowledge in Logic Programs with Uncertainty
Loyer Y, Straccia U
Many frameworks have been proposed to manage uncertain information in logic programming. Essentially, they differ in the underlying notion of uncertainty and how these uncertainty values, associated to rules and facts, are managed. The goal of this paper is to allow the reasoning with non-uniform default assumptions, i.e with any arbitrary assignment of default values to the atoms. Informally, rather than to rely on the same default certainty value for all atoms, we allow arbitrary assignments to complete information. To this end, we define both epistemologically and computationally the semantics according to any given assumption. For reasons of generality, we present our work in the framework presented in [Lakshmanan01] as a unifying umbrella for many of the proposed approaches to the management of uncertainty in logic programming. Our extension is conservative in the following sense: (i) if we restrict our attention to the usual uniform Open World Assumption, then the semantics reduces to the Kripke-Kleene semantics, and (ii) if we restrict our attention to the uniform Closed World Assumption, then our semantics reduces to the well-founded semantics.DOI: 10.1007/978-3-540-24599-5_32
Metrics:
Loyer Y, Straccia U
Many frameworks have been proposed to manage uncertain information in logic programming. Essentially, they differ in the underlying notion of uncertainty and how these uncertainty values, associated to rules and facts, are managed. The goal of this paper is to allow the reasoning with non-uniform default assumptions, i.e with any arbitrary assignment of default values to the atoms. Informally, rather than to rely on the same default certainty value for all atoms, we allow arbitrary assignments to complete information. To this end, we define both epistemologically and computationally the semantics according to any given assumption. For reasons of generality, we present our work in the framework presented in [Lakshmanan01] as a unifying umbrella for many of the proposed approaches to the management of uncertainty in logic programming. Our extension is conservative in the following sense: (i) if we restrict our attention to the usual uniform Open World Assumption, then the semantics reduces to the Kripke-Kleene semantics, and (ii) if we restrict our attention to the uniform Closed World Assumption, then our semantics reduces to the well-founded semantics.DOI: 10.1007/978-3-540-24599-5_32
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gaia.isti.cnr.it | doi.org | CNR IRIS | CNR IRIS | link.springer.com
2008
Conference article
Open Access
Fuzzy bilateral matchmaking in e-marketplaces
Ragone A, Straccia U, Bobillo F, Di Noia T, Di Sciascio E, Donini F
We present a novel Fuzzy Description Logic (DL) based approach to automate matchmaking in e-marketplaces. We model traders' preferences with the aid of Fuzzy DLs and, given a request, use utility values computed w.r.t. Pareto agreements to rank a set of offers. In particular, we introduce an expressive Fuzzy DL, extended with concrete domains in order to handle numerical, as well as non numerical features, and to deal with vagueness in buyer/seller preferences. Hence, agents can express preferences as eg textit{I am searching for a passenger car costing about 22000euro, yet if the car has a GPS system and more than two-year warranty I can spend up to 25000euro}. Noteworthy our matchmaking approach, among all the possible matches, chooses the mutually beneficial ones.DOI: 10.1007/978-3-540-85567-5_37
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Ragone A, Straccia U, Bobillo F, Di Noia T, Di Sciascio E, Donini F
We present a novel Fuzzy Description Logic (DL) based approach to automate matchmaking in e-marketplaces. We model traders' preferences with the aid of Fuzzy DLs and, given a request, use utility values computed w.r.t. Pareto agreements to rank a set of offers. In particular, we introduce an expressive Fuzzy DL, extended with concrete domains in order to handle numerical, as well as non numerical features, and to deal with vagueness in buyer/seller preferences. Hence, agents can express preferences as eg textit{I am searching for a passenger car costing about 22000euro, yet if the car has a GPS system and more than two-year warranty I can spend up to 25000euro}. Noteworthy our matchmaking approach, among all the possible matches, chooses the mutually beneficial ones.DOI: 10.1007/978-3-540-85567-5_37
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