Semantic Matchmaking as Non-Monotonic Reasoning: A Description Logic Approach

Matchmaking arises when supply and demand meet in an electronic marketplace, or when agents search for a web service to perform some task, or even when recruiting agencies match curricula and job profiles. In such open environments, the objective of a matchmaking process is to discover best available offers to a given request. We address the problem of matchmaking from a knowledge representation perspective, with a formalization based on Description Logics. We devise Concept Abduction and Concept Contraction as non-monotonic inferences in Description Logics suitable for modeling matchmaking in a logical framework, and prove some related complexity results. We also present reasonable algorithms for semantic matchmaking based on the devised inferences, and prove that they obey to some commonsense properties. Finally, we report on the implementation of the proposed matchmaking framework, which has been used both as a mediator in e-marketplaces and for semantic web services discovery

Decidable Reasoning in Terminological Knowledge Representation Systems

Terminological knowledge representation systems (TKRSs) are tools for designing and using knowledge bases that make use of terminological languages (or concept languages). We analyze from a theoretical point of view a TKRS whose capabilities go beyond the ones of presently available TKRSs. The new features studied, often required in practical applications, can be summarized in three main points. First, we consider a highly expressive terminological language, called ALCNR, including general complements of concepts, number restrictions and role conjunction. Second, we allow to express inclusion statements between general concepts, and terminological cycles as a particular case. Third, we prove the decidability of a number of desirable TKRS-deduction services (like satisfiability, subsumption and instance checking) through a sound, complete and terminating calculus for reasoning in ALCNR-knowledge bases. Our calculus extends the general technique of constraint systems. As a byproduct of the proof, we get also the result that inclusion statements in ALCNR can be simulated by terminological cycles, if descriptive semantics is adopted.Comment: See http://www.jair.org/ for any accompanying file

A Neutrosophic Description Logic

Description Logics (DLs) are appropriate, widely used, logics for managing structured knowledge. They allow reasoning about individuals and concepts, i.e. set of individuals with common properties. Typically, DLs are limited to dealing with crisp, well defined concepts. That is, concepts for which the problem whether an individual is an instance of it is yes/no question. More often than not, the concepts encountered in the real world do not have a precisely defined criteria of membership: we may say that an individual is an instance of a concept only to a certain degree, depending on the individual's properties. The DLs that deal with such fuzzy concepts are called fuzzy DLs. In order to deal with fuzzy, incomplete, indeterminate and inconsistent concepts, we need to extend the fuzzy DLs, combining the neutrosophic logic with a classical DL. In particular, concepts become neutrosophic (here neutrosophic means fuzzy, incomplete, indeterminate, and inconsistent), thus reasoning about neutrosophic concepts is supported. We'll define its syntax, its semantics, and describe its properties.Comment: 18 pages. Presented at the IEEE International Conference on Granular Computing, Georgia State University, Atlanta, USA, May 200

Structural Subsumption for ALN

Aus der Einleitung: „In this paper, we reuse the representation formalism `description graph' in order to characterize subsumption of ALN-concepts. The description logic ALN allows for conjunction, valuerestrictions, number restrictions, and primitive negation. Since Classic allows for more constructors than ALN, e.g., equality restrictions an attribute chains by the constructor SAME-AS,we can confine the notion of description graphs from [BP94]. On the other hand, ALN explicitly allows for primitive negation which yields another possibility { besides conflicting number restrictions { to express inconsistency. Thus, we have to modify the notion of canonical description graphs in order to cope with inconsistent concepts in the structural characterization of subsumption. It turns out that the description graphs obtained from ALN-concepts are in fact trees. A canonical graph is a deterministic tree. The conditions required by the structural characterization of subsumption on these trees can be tested by an eficient algorithm, i.e., we obtain an algorithm deciding subsumption of C and D in time polynomial in the size of C and D. The report is structured as follows. In the preliminaries, we define syntax and semantics of the description logic ALN as well as the inference problem of subsumption. In Section 3, we introduce description graphs, the data structure our structural subsumption algorithm is working on. Besides syntax and semantics also an algorithm for translating ALN-concepts into description graphs is given. Thereafter, we present the main result of this report in Section 6, a characterization of subsumption of ALN-concepts by a structural comparison of corresponding description graphs. Furthermore, a structural subsumption algorithm can be found in Section 6.2. In the last section we summarize our results and give an outlook to further applications of structural subsumption in terminological knowledge representation systems

Closed Terminologies and Temporal Reasoning in Description Logic for Concept and Plan Recognition

Description logics are knowledge representation formalisms in the tradition of frames and semantic networks, but with an emphasis on formal semantics. A terminology contains descriptions of concepts, such as UNIVERSITY, which are automatically classified ina taxonomy via subsumption inferences. Individuals such as COLUMBIA are described in terms of those concepts. This thesis enhances the scope and utility of description logics by exploiting new completeness assumptions during problem solving and by extending the expressiveness of descriptions. First, we introduce a predictive concept recognition methodology based on a new closed terminology assumption (CTA). The terminology is dynamically partitioned by modalities (necessary, optional, and impossible) with respect to individuals as they are specified. In our interactive configuration application, a user incrementally specifies an individual computer system and its components in collaboration with a configuration engine. Choices can be made in any order and at any level of abstraction. We distinguish between abstract and concrete concepts to formally define when an individual's description may be considered finished. We also exploit CTA, together with the terminology's subsumption-based organization, to efficiently track the types of systems and components consistent with current choices, infer additional constraints on current choices, and appropriately restrict future choices. Thus, we can help focus the efforts of both user and configuration engine. This work is implemented in the K-REP system. Second, we show that a new class of complex descriptions can be formed via constraint networks over standard descriptions. For example, we model plans as constraint networks whose nodes represent actions.Arcs represent qualitative and metric temporal constraints, plusco-reference constraints, between actions. By combining terminological reasoning with constraint satisfaction techniques, subsumption is extended to constraint networks, allowing automatic classification of a plan library. This work is implemented in the T-REX system, which integrates and builds upon an existing description logic system (K-REP or CLASSIC) and temporal reasoner (MATS). Finally, we combine the preceding, orthogonal results to conduct predictive recognition of constraint network concepts. As an example,this synthesis enables a new approach to deductive plan recognition,illustrated with travel plans. This work is also realized in T-REX

Extensible Knowledge Representation: the Case of Description Reasoners

This paper offers an approach to extensible knowledge representation and reasoning for a family of formalisms known as Description Logics. The approach is based on the notion of adding new concept constructors, and includes a heuristic methodology for specifying the desired extensions, as well as a modularized software architecture that supports implementing extensions. The architecture detailed here falls in the normalize-compared paradigm, and supports both intentional reasoning (subsumption) involving concepts, and extensional reasoning involving individuals after incremental updates to the knowledge base. The resulting approach can be used to extend the reasoner with specialized notions that are motivated by specific problems or application areas, such as reasoning about dates, plans, etc. In addition, it provides an opportunity to implement constructors that are not currently yet sufficiently well understood theoretically, but are needed in practice. Also, for constructors that are provably hard to reason with (e.g., ones whose presence would lead to undecidability), it allows the implementation of incomplete reasoners where the incompleteness is tailored to be acceptable for the application at hand

Matching Concept Descriptions with Existential Restrictions

Matching of concepts with variables (concept patterns) is a relatively new operation that has been introduced in the context of description logics, originally to help filter out unimportant aspects of large concepts appearing in industrial-strength knowledge bases. Previous work has concentrated on (sub-)languages of CLASSIC, which in particular do not allow for existential restrictions. In this work, we present sound and complete decision algorithms for the solvability of matching problems and for computing sets of matchers for matching problems in description logics with existential restrictions

Description Logics as Ontology Languages for the Semantic Web

The vision of a Semantic Web has recently drawn considerable attention, both from academia and industry. Description logics are often named as one of the tools that can support the Semantic Web and thus help to make this vision reality. In this paper, we describe what description logics are and what they can do for the Semantic Web. Descriptions logics are very useful for defining, integrating, and maintaining ontologies, which provide the Semantic Web with a common understanding of the basic semantic concepts used to annotate Web pages. We also argue that, without the last decade of basic research in this area, description logics could not play such an important rˆole in this domain