HAL (Le Centre pour la Communication Scientifique Directe), 2011
This paper introduces a new type of database queries involving preferences. The idea is to consid... more This paper introduces a new type of database queries involving preferences. The idea is to consider competitive conditional preference clauses structured as a tree, of the type "preferably P 1 or • • • or P n ; if P 1 then preferably P 1,1 or. . .; if P 2 then preferably P 2,1 or. .. ," where the P i s are not exclusive (thus the notion of competition). The paper defines two possible interpretations of such queries and outlines two evaluation techniques which follow from them.
International Journal of Intelligent Computing and Cybernetics, Jun 12, 2017
PurposeTime modeling is a crucial feature in many application domains. However, temporal informat... more PurposeTime modeling is a crucial feature in many application domains. However, temporal information often is not crisp, but is subjective and fuzzy. The purpose of this paper is to address the issue related to the modeling and handling of imperfection inherent to both temporal relations and intervals.Design/methodology/approachOn the one hand, fuzzy extensions of Allen temporal relations are investigated and, on the other hand, extended temporal relations to define the positions of two fuzzy time intervals are introduced. Then, a database system, called Fuzzy Temporal Information Management and Exploitation (Fuzz-TIME), is developed for the purpose of processing fuzzy temporal queries.FindingsTo evaluate the proposal, the authors have implemented a Fuzz-TIME system and created a fuzzy historical database for the querying purpose. Some demonstrative scenarios from history domain are proposed and discussed.Research limitations/implicationsThe authors have conducted some experiments on archaeological data to show the effectiveness of the Fuzz-TIME system. However, thorough experiments on large-scale databases are highly desirable to show the behavior of the tool with respect to the performance and time execution criteria.Practical implicationsThe tool developed (Fuzz-TIME) can have many practical applications where time information has to be dealt with. In particular, in several real-world applications like history, medicine, criminal and financial domains, where time is often perceived or expressed in an imprecise/fuzzy manner.Social implicationsThe social implications of this work can be expected, more particularly, in two domains: in the museum to manage, exploit and analysis the piece of information related to archives and historic data; and in the hospitals/medical organizations to deal with time information inherent to data about patients and diseases.Originality/valueThis paper presents the design and characterization of a novel and intelligent database system to process and manage the imperfection inherent to both temporal relations and intervals.
HAL (Le Centre pour la Communication Scientifique Directe), 2010
The paper presents a new approach to database preferences queries, where preferences are represen... more The paper presents a new approach to database preferences queries, where preferences are represented in a possibilistic logic manner, using symbolic weights. The symbolic weights may be processed without assessing their precise value, which leaves the freedom for the user to not specify any priority among the preferences. The user may also enforce a (partial) ordering between them, if necessary. The approach can be related to the processing of fuzzy queries whose components are conditionally weighted in terms of importance. Here, importance levels are symbolically processed, and refinements of both Pareto ordering and minimum ordering are used. The representational power of the proposed setting is stressed, while the approach is compared with database Best operator-like methods and with the CP-net approach developed in artificial intelligence. The paper also provides a structured and rather broad overview of the different lines of research in the literature dealing with the handling of preferences in database queries.
Communications in computer and information science, 2016
In many fields of automated information processing it becomes crucial to consider imprecise, unce... more In many fields of automated information processing it becomes crucial to consider imprecise, uncertain or inconsistent pieces of information. Therefore, integrating uncertainty factors in argumentation theory is of paramount importance. Recently, several argumentation based approaches have emerged to model uncertain data with probabilities. In this paper, we propose a new argumentation system called evidential argumentation framework that takes into account imprecision and uncertainty modeled by means of evidence theory. Indeed, evidence theory brings new semantics since arguments represent expert opinions with several weighted alternatives. Then, the evidential argumentation framework is studied in the light of both Smets and Demspter-Shafer interpretations of evidence theory. For each interpretation, we generalize Dung’s standard semantics with illustrative examples. We also investigate several preference criteria for pairwise comparison of extensions in order to select the ones that represent potential solutions to a given decision making problem.
Annals of Mathematics and Artificial Intelligence, Dec 1, 2011
This note corrects a claim made in the above-mentioned paper about the exact representation of a ... more This note corrects a claim made in the above-mentioned paper about the exact representation of a conditional preference network by means of a possibilistic logic base with partially ordered symbolic weights. We provide a counterexample that shows that the possibilistic logic representation is indeed not always exact. This is the basis of a short discussion on the difficulty of obtaining an exact representation. This note corrects a claim made in [6] about the representation of Conditional Preference networks (CP-nets for short) [1] by means of a possibilistic logic base [2], as well as a similar claim in [7, 8]. A CP-net encodes a set of preference statements concerning the values of Boolean decision variables, conditioned on the values of other Boolean decision variables that influence the former. More formally, let V = {X 1 , • • • , X n } be a set of Boolean variables. We denote by Ast (S) the set of interpretations of variables of S (⊆ V). Definition 1 A CP-net N over V = {X 1 , • • • , X n } is a directed graph with nodes X 1 , • • • , X n , and there is a directed edge from X i to X j if the preference about the value X j depends on the value of X i. Each node X i ∈ V is associated with a conditional preference table CP T i that associates a strict preference (x i > ¬x i or ¬x i > x i
In this paper we discuss and propose certain opportunities provided by the Semantic Web technolog... more In this paper we discuss and propose certain opportunities provided by the Semantic Web technologies in the view of improving the learning content management. In order to express each metadata in the most appropriate metadata standard format, there could be integrated the general ...
While uncertainty can't be ignored in real-world problems, there is almost no research work a... more While uncertainty can't be ignored in real-world problems, there is almost no research work addressing this issue in the recommender systems framework, especially all that relates to user ratings preferences. Indeed, the subjectivity of user's rating and his/her changing preferences over time, make them subject to uncertainty. Usually, user's imprecise rating for an item (product or service) is time-dependent information and generally provided much later. Meantime the item may change either by degrading or improving its inherent quality. The rating therefore may deviate, since it doesn't describe faithfully the actual current state of the item. This deviation leads to a form of uncertainty on user preferences that we handle in this paper. We show that uncertainty is an ubiquitous aspect in building recommender systems and its taking into account can help predicting the most accurate items by improving their certainty degrees.
Proceedings of ... IEEE International Conference on Fuzzy Systems, Jun 1, 2007
Fuzzy modifiers are unary operators on fuzzy sets aiming at transforming a fuzzy set into another... more Fuzzy modifiers are unary operators on fuzzy sets aiming at transforming a fuzzy set into another. In this paper, we propose a new approach to construct representation for fuzzy modifiers. The approach relies on a tolerance relation modeled by a suitable parameterized proximity relation. The newly introduced fuzzy modifiers are not only endowed with clear semantics, but they result in
L'interrogation de bases de données, dont les dimensions ne cessent de croître, se heurte fréquem... more L'interrogation de bases de données, dont les dimensions ne cessent de croître, se heurte fréquemment au problème de la gestion des réponses pléthoriques. Une des approches envisageables pour réduire l'ensemble des résultats retournés et le rendre exploitable est de contraindre la requête initiale par l'ajout de nouvelles conditions. L'approche présentée dans cet article s'appuie sur l'identification de liens de corrélation entre prédicats associés aux attributs de la relation concernée. La requête initiale peut ainsi être intensifiée automatiquement ou par validation de l'utilisateur à travers l'ajout de prédicats proches sémantiquement de ceux spécifiés.
Modern enterprises are increasingly moving towards a service oriented architecture for data shari... more Modern enterprises are increasingly moving towards a service oriented architecture for data sharing by putting their data sources behind services, thereby providing an interoperable way to interact with their data. This class of services is known as DaaS ( Data-as-a-Service ) services. DaaS Composition is a powerful solution to answer the user's complex queries by combining primitive DaaS services. User preferences are a key aspect that must be considered in the service composition process. A more general and suitable approach to model preferences is based on fuzzy sets theory [3]. Fuzzy sets are very well suited to the interpretation of linguistic terms and constitute a convenient way for a user to express her/his preferences. For example, when expressing preferences about the price of a car, users often employ fuzzy terms like rather cheap, affordable , etc. However as DaaS services proliferate, a large number of candidate compositions that would use different (most likely competing) services may be used to answer the same query. Hence, it is important to set up an effective service composition framework that would identify and retrieve the most relevant services and return the top- k compositions according to the user preferences.
HAL (Le Centre pour la Communication Scientifique Directe), 2002
This paper proposes a fuzzy set-based approach for handling relative orders of magnitude stated i... more This paper proposes a fuzzy set-based approach for handling relative orders of magnitude stated in terms of closeness and negligibility relations. At the semantic level, these relations are represented by means of fuzzy relations controlled by tolerance parameters. A set of sound inference rules, involving the tolerance parameters, is provided, in full accordance with the combination/projection principle underlying the approximate reasoning method of Zadeh. These rules ensure a local propagation of fuzzy closeness and negligibility relations. A numerical semantics is then attached to the symbolic computation process. Required properties of the tolerance parameter are investigated, in order to preserve the validity of the produced conclusions. The effect of the chaining of rules in the inference process can be controlled through the gradual deterioration of closeness and negligibility relations involved in the produced conclusions. Finally, qualitative reasoning based on fuzzy closeness and negligibility relations is used for simplifying equations and solving them in an approximate way, as often done by engineers who reason about a mathematical model. The problem of handling qualitative probabilities in reasoning under uncertainty is also investigated in this perspective.
Why am I not getting the right answer?" is a question many Knowledge Base users may ask themselve... more Why am I not getting the right answer?" is a question many Knowledge Base users may ask themselves. In particular, novice users can easily make mistakes and find differences between the answer they expected and the answer they got. This problem is known as the unsatisfactory answer problem. A subproblem, where no answers are returned, has been widely studied and identifying failure causes can help users modify their queries to fit their requirements. But users may be unhappy with their results for multiple other reasons: they may be overwhelmed by too many answers, expect a particular answer that is not included, or even encounter a combination of these problems. In this paper, we classify the various types of unsatisfactory answers, and propose algorithms to compute generalized failure causes. We evaluate the performance of our algorithms and show that they perform comparably to existing problemspecific methods, while being more extensive.
When querying Knowledge Bases (KBs), users are faced with large sets of data, often without knowi... more When querying Knowledge Bases (KBs), users are faced with large sets of data, often without knowing their underlying structures. It follows that users may make mistakes when formulating their queries, therefore receiving an unhelpful response. In this paper, we address the plethoric answers problem, the situation where the user query produces significantly more results than the user was expecting. The common approach to solving this problem, i.e. the top-K approach, reduces the query's result size by applying various criteria to select only some answers. This selection is performed without considering the causes producing plethoric answers, and can therefore miss an underlying issue within the query. We deal with this problem by proposing an approach that identifies the parts of the failing query, called Minimal Failure Inducing Subqueries (MFIS), that cause plethoric answers. As long as the query contains an MFIS, it will fail to reach a sufficiently low amount of answers. Thus, thanks to these MFIS, interactive and automatic approaches can be set up to help the user in reformulating their query. The dual notion of MFIS, called Maximal Succeeding Subqueries (XSS), is also useful. They provide queries with a maximal number of parts of the original query that return non plethoric answers. Our goal is to compute MFIS and XSS efficiently, so that they may be used to solve the plethoric answers problem. We
HAL (Le Centre pour la Communication Scientifique Directe), 2011
This paper introduces a new type of database queries involving preferences. The idea is to consid... more This paper introduces a new type of database queries involving preferences. The idea is to consider competitive conditional preference clauses structured as a tree, of the type "preferably P 1 or • • • or P n ; if P 1 then preferably P 1,1 or. . .; if P 2 then preferably P 2,1 or. .. ," where the P i s are not exclusive (thus the notion of competition). The paper defines two possible interpretations of such queries and outlines two evaluation techniques which follow from them.
International Journal of Intelligent Computing and Cybernetics, Jun 12, 2017
PurposeTime modeling is a crucial feature in many application domains. However, temporal informat... more PurposeTime modeling is a crucial feature in many application domains. However, temporal information often is not crisp, but is subjective and fuzzy. The purpose of this paper is to address the issue related to the modeling and handling of imperfection inherent to both temporal relations and intervals.Design/methodology/approachOn the one hand, fuzzy extensions of Allen temporal relations are investigated and, on the other hand, extended temporal relations to define the positions of two fuzzy time intervals are introduced. Then, a database system, called Fuzzy Temporal Information Management and Exploitation (Fuzz-TIME), is developed for the purpose of processing fuzzy temporal queries.FindingsTo evaluate the proposal, the authors have implemented a Fuzz-TIME system and created a fuzzy historical database for the querying purpose. Some demonstrative scenarios from history domain are proposed and discussed.Research limitations/implicationsThe authors have conducted some experiments on archaeological data to show the effectiveness of the Fuzz-TIME system. However, thorough experiments on large-scale databases are highly desirable to show the behavior of the tool with respect to the performance and time execution criteria.Practical implicationsThe tool developed (Fuzz-TIME) can have many practical applications where time information has to be dealt with. In particular, in several real-world applications like history, medicine, criminal and financial domains, where time is often perceived or expressed in an imprecise/fuzzy manner.Social implicationsThe social implications of this work can be expected, more particularly, in two domains: in the museum to manage, exploit and analysis the piece of information related to archives and historic data; and in the hospitals/medical organizations to deal with time information inherent to data about patients and diseases.Originality/valueThis paper presents the design and characterization of a novel and intelligent database system to process and manage the imperfection inherent to both temporal relations and intervals.
HAL (Le Centre pour la Communication Scientifique Directe), 2010
The paper presents a new approach to database preferences queries, where preferences are represen... more The paper presents a new approach to database preferences queries, where preferences are represented in a possibilistic logic manner, using symbolic weights. The symbolic weights may be processed without assessing their precise value, which leaves the freedom for the user to not specify any priority among the preferences. The user may also enforce a (partial) ordering between them, if necessary. The approach can be related to the processing of fuzzy queries whose components are conditionally weighted in terms of importance. Here, importance levels are symbolically processed, and refinements of both Pareto ordering and minimum ordering are used. The representational power of the proposed setting is stressed, while the approach is compared with database Best operator-like methods and with the CP-net approach developed in artificial intelligence. The paper also provides a structured and rather broad overview of the different lines of research in the literature dealing with the handling of preferences in database queries.
Communications in computer and information science, 2016
In many fields of automated information processing it becomes crucial to consider imprecise, unce... more In many fields of automated information processing it becomes crucial to consider imprecise, uncertain or inconsistent pieces of information. Therefore, integrating uncertainty factors in argumentation theory is of paramount importance. Recently, several argumentation based approaches have emerged to model uncertain data with probabilities. In this paper, we propose a new argumentation system called evidential argumentation framework that takes into account imprecision and uncertainty modeled by means of evidence theory. Indeed, evidence theory brings new semantics since arguments represent expert opinions with several weighted alternatives. Then, the evidential argumentation framework is studied in the light of both Smets and Demspter-Shafer interpretations of evidence theory. For each interpretation, we generalize Dung’s standard semantics with illustrative examples. We also investigate several preference criteria for pairwise comparison of extensions in order to select the ones that represent potential solutions to a given decision making problem.
Annals of Mathematics and Artificial Intelligence, Dec 1, 2011
This note corrects a claim made in the above-mentioned paper about the exact representation of a ... more This note corrects a claim made in the above-mentioned paper about the exact representation of a conditional preference network by means of a possibilistic logic base with partially ordered symbolic weights. We provide a counterexample that shows that the possibilistic logic representation is indeed not always exact. This is the basis of a short discussion on the difficulty of obtaining an exact representation. This note corrects a claim made in [6] about the representation of Conditional Preference networks (CP-nets for short) [1] by means of a possibilistic logic base [2], as well as a similar claim in [7, 8]. A CP-net encodes a set of preference statements concerning the values of Boolean decision variables, conditioned on the values of other Boolean decision variables that influence the former. More formally, let V = {X 1 , • • • , X n } be a set of Boolean variables. We denote by Ast (S) the set of interpretations of variables of S (⊆ V). Definition 1 A CP-net N over V = {X 1 , • • • , X n } is a directed graph with nodes X 1 , • • • , X n , and there is a directed edge from X i to X j if the preference about the value X j depends on the value of X i. Each node X i ∈ V is associated with a conditional preference table CP T i that associates a strict preference (x i > ¬x i or ¬x i > x i
In this paper we discuss and propose certain opportunities provided by the Semantic Web technolog... more In this paper we discuss and propose certain opportunities provided by the Semantic Web technologies in the view of improving the learning content management. In order to express each metadata in the most appropriate metadata standard format, there could be integrated the general ...
While uncertainty can't be ignored in real-world problems, there is almost no research work a... more While uncertainty can't be ignored in real-world problems, there is almost no research work addressing this issue in the recommender systems framework, especially all that relates to user ratings preferences. Indeed, the subjectivity of user's rating and his/her changing preferences over time, make them subject to uncertainty. Usually, user's imprecise rating for an item (product or service) is time-dependent information and generally provided much later. Meantime the item may change either by degrading or improving its inherent quality. The rating therefore may deviate, since it doesn't describe faithfully the actual current state of the item. This deviation leads to a form of uncertainty on user preferences that we handle in this paper. We show that uncertainty is an ubiquitous aspect in building recommender systems and its taking into account can help predicting the most accurate items by improving their certainty degrees.
Proceedings of ... IEEE International Conference on Fuzzy Systems, Jun 1, 2007
Fuzzy modifiers are unary operators on fuzzy sets aiming at transforming a fuzzy set into another... more Fuzzy modifiers are unary operators on fuzzy sets aiming at transforming a fuzzy set into another. In this paper, we propose a new approach to construct representation for fuzzy modifiers. The approach relies on a tolerance relation modeled by a suitable parameterized proximity relation. The newly introduced fuzzy modifiers are not only endowed with clear semantics, but they result in
L'interrogation de bases de données, dont les dimensions ne cessent de croître, se heurte fréquem... more L'interrogation de bases de données, dont les dimensions ne cessent de croître, se heurte fréquemment au problème de la gestion des réponses pléthoriques. Une des approches envisageables pour réduire l'ensemble des résultats retournés et le rendre exploitable est de contraindre la requête initiale par l'ajout de nouvelles conditions. L'approche présentée dans cet article s'appuie sur l'identification de liens de corrélation entre prédicats associés aux attributs de la relation concernée. La requête initiale peut ainsi être intensifiée automatiquement ou par validation de l'utilisateur à travers l'ajout de prédicats proches sémantiquement de ceux spécifiés.
Modern enterprises are increasingly moving towards a service oriented architecture for data shari... more Modern enterprises are increasingly moving towards a service oriented architecture for data sharing by putting their data sources behind services, thereby providing an interoperable way to interact with their data. This class of services is known as DaaS ( Data-as-a-Service ) services. DaaS Composition is a powerful solution to answer the user's complex queries by combining primitive DaaS services. User preferences are a key aspect that must be considered in the service composition process. A more general and suitable approach to model preferences is based on fuzzy sets theory [3]. Fuzzy sets are very well suited to the interpretation of linguistic terms and constitute a convenient way for a user to express her/his preferences. For example, when expressing preferences about the price of a car, users often employ fuzzy terms like rather cheap, affordable , etc. However as DaaS services proliferate, a large number of candidate compositions that would use different (most likely competing) services may be used to answer the same query. Hence, it is important to set up an effective service composition framework that would identify and retrieve the most relevant services and return the top- k compositions according to the user preferences.
HAL (Le Centre pour la Communication Scientifique Directe), 2002
This paper proposes a fuzzy set-based approach for handling relative orders of magnitude stated i... more This paper proposes a fuzzy set-based approach for handling relative orders of magnitude stated in terms of closeness and negligibility relations. At the semantic level, these relations are represented by means of fuzzy relations controlled by tolerance parameters. A set of sound inference rules, involving the tolerance parameters, is provided, in full accordance with the combination/projection principle underlying the approximate reasoning method of Zadeh. These rules ensure a local propagation of fuzzy closeness and negligibility relations. A numerical semantics is then attached to the symbolic computation process. Required properties of the tolerance parameter are investigated, in order to preserve the validity of the produced conclusions. The effect of the chaining of rules in the inference process can be controlled through the gradual deterioration of closeness and negligibility relations involved in the produced conclusions. Finally, qualitative reasoning based on fuzzy closeness and negligibility relations is used for simplifying equations and solving them in an approximate way, as often done by engineers who reason about a mathematical model. The problem of handling qualitative probabilities in reasoning under uncertainty is also investigated in this perspective.
Why am I not getting the right answer?" is a question many Knowledge Base users may ask themselve... more Why am I not getting the right answer?" is a question many Knowledge Base users may ask themselves. In particular, novice users can easily make mistakes and find differences between the answer they expected and the answer they got. This problem is known as the unsatisfactory answer problem. A subproblem, where no answers are returned, has been widely studied and identifying failure causes can help users modify their queries to fit their requirements. But users may be unhappy with their results for multiple other reasons: they may be overwhelmed by too many answers, expect a particular answer that is not included, or even encounter a combination of these problems. In this paper, we classify the various types of unsatisfactory answers, and propose algorithms to compute generalized failure causes. We evaluate the performance of our algorithms and show that they perform comparably to existing problemspecific methods, while being more extensive.
When querying Knowledge Bases (KBs), users are faced with large sets of data, often without knowi... more When querying Knowledge Bases (KBs), users are faced with large sets of data, often without knowing their underlying structures. It follows that users may make mistakes when formulating their queries, therefore receiving an unhelpful response. In this paper, we address the plethoric answers problem, the situation where the user query produces significantly more results than the user was expecting. The common approach to solving this problem, i.e. the top-K approach, reduces the query's result size by applying various criteria to select only some answers. This selection is performed without considering the causes producing plethoric answers, and can therefore miss an underlying issue within the query. We deal with this problem by proposing an approach that identifies the parts of the failing query, called Minimal Failure Inducing Subqueries (MFIS), that cause plethoric answers. As long as the query contains an MFIS, it will fail to reach a sufficiently low amount of answers. Thus, thanks to these MFIS, interactive and automatic approaches can be set up to help the user in reformulating their query. The dual notion of MFIS, called Maximal Succeeding Subqueries (XSS), is also useful. They provide queries with a maximal number of parts of the original query that return non plethoric answers. Our goal is to compute MFIS and XSS efficiently, so that they may be used to solve the plethoric answers problem. We
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