Approximate reasoning using terminological models

Term Subsumption Systems (TSS) form a knowledge-representation scheme in AI that can express the defining characteristics of concepts through a formal language that has a well-defined semantics and incorporates a reasoning mechanism that can deduce whether one concept subsumes another. However, TSS's have very limited ability to deal with the issue of uncertainty in knowledge bases. The objective of this research is to address issues in combining approximate reasoning with term subsumption systems. To do this, we have extended an existing AI architecture (CLASP) that is built on the top of a term subsumption system (LOOM). First, the assertional component of LOOM has been extended for asserting and representing uncertain propositions. Second, we have extended the pattern matcher of CLASP for plausible rule-based inferences. Third, an approximate reasoning model has been added to facilitate various kinds of approximate reasoning. And finally, the issue of inconsistency in truth values due to inheritance is addressed using justification of those values. This architecture enhances the reasoning capabilities of expert systems by providing support for reasoning under uncertainty using knowledge captured in TSS. Also, as definitional knowledge is explicit and separate from heuristic knowledge for plausible inferences, the maintainability of expert systems could be improved

Automatic view schema generation in object-oriented databases

An object-oriented data schema is a complex structure of classes interrelated via generalization and property decomposition relationships. We define an object-oriented view to be a virtual schema graph with possibly restructured generalization and decomposition hierarchies - rather than just one individual virtual class as proposed in the literature. In this paper, we propose a methodology, called MultiView, for supporting multiple such view schemata. MultiView is anchored on the following complementary ideas: (a) the view definer derives virtual classes and then integrates them into one consistent global schema graph and (b) the view definer specifies arbitrarily complex view schemata on this augmented global schema. The focus of this paper is, however, on the second, less explored, issue. This part of the view definition is performed using the following two steps: (1) view class selection and (2) view schema graph generation. For the first, we have developed a view definition language that can be used by the view definer to specify the selection of the desired view classes from the global schema. For the second, we have developed two algorithms that automatically augment the set of selected view classes to generate a complete, minimal and consistent view class generalization hierarchy. The first algorithm has linear complexity but it assumes that the global schema graph is a tree. The second algorithm overcomes this restricting assumption and thus allows for multiple inheritance, but it does so at the cost of a higher complexity

MultiView : a methodology for supporting multiple view schemata in object-oriented databases

It has been widely recognized that object-oriented database (OODB) technology needs to be extended to provide a mechanism similar to views in relational database systems. We define an object-oriented view to be an arbitrarily complex virtual schema graph with possibly restructured generalization and decomposition hierarchies - rather than just one virtual class as has been proposed in the literature. In this paper, we propose a methodology, called MultiView, for supporting multiple such view schemata. MultiView breaks the schema design task into the following independent and well-defined subtasks: (1) the customization of type descriptions and object sets of existing classes by deriving virtual classes, (2) the integration of all derived classes into one consistent global schema graph, and (3) the definition of arbitrarily complex view schemata on this augmented global schema. For the first task of MultiView, we define a set of object algebra operators that can be used by the view definer for class customization. For the second task of MultiView, we propose an algorithm that automatically integrates these newly derived virtual classes into the global schema. We solve the third task of MultiView by first letting the view definer explicitly select the desired view classes from the global schema using a view definition language and then by automatically generating a view class hierarchy for these selected classes. In addition, we present algorithms that verify the closure property of a view and, if found to be incomplete, transform it into a closed, yet minimal, view. In this paper, we introduce the fundamental concept of view independence and show MultiView to be view independent. We also outline implementation techniques for realizing MultiView with existing OODB technology

Partially shared views : a scheme for communicating among groups that use different type hierarchies

"March 1988."Includes bibliographical references (p. [27]).Research supported in part by Wang Laboratories, Inc., Xerox Corporation, General Motors, and Bankers Trust Company.Jintae Lee, Thomas W. Malone

Partially shared views : a scheme for communicating among groups that use different type hierarchies

Includes bibliographical references (p. 34-36).Supported by Digital Equipment Corp., the National Science Foundation, Wang Laboratories, Inc., Xerox Corporation, General Motors and Bankers Trust Company.Jintae Lee, Thomas W. Malone

How can groups communicate when they use different languages? : translating between partially shared type heirarchies

Includes bibliographical references (p. 1-3, second group).Supported in part by DARPA, the National Science Foundation, Wang Laboratories, Inc., Xerox Corporation, General Motors, and Bankers Trust Company.Jintae Lee, Thomas W. Malone

Abstract Representation of Music: A Type-Based Knowledge Representation Framework

The wholesale efficacy of computer-based music research is contingent on the sharing and reuse of information and analysis methods amongst researchers across the constituent disciplines. However, computer systems for the analysis and manipulation of musical data are generally not interoperable. Knowledge representation has been extensively used in the domain of music to harness the benefits of formal conceptual modelling combined with logic based automated inference. However, the available knowledge representation languages lack sufficient logical expressivity to support sophisticated musicological concepts. In this thesis we present a type-based framework for abstract representation of musical knowledge. The core of the framework is a multiple-hierarchical information model called a constituent structure, which accommodates diverse kinds of musical information. The framework includes a specification logic for expressing formal descriptions of the components of the representation. We give a formal specification for the framework in the Calculus of Inductive Constructions, an expressive logical language which lends itself to the abstract specification of data types and information structures. We give an implementation of our framework using Semantic Web ontologies and JavaScript. The ontologies capture the core structural aspects of the representation, while the JavaScript tools implement the functionality of the abstract specification. We describe how our framework supports three music analysis tasks: pattern search and discovery, paradigmatic analysis and hierarchical set-class analysis, detailing how constituent structures are used to represent both the input and output of these analyses including sophisticated structural annotations. We present a simple demonstrator application, built with the JavaScript tools, which performs simple analysis and visualisation of linked data documents structured by the ontologies. We conclude with a summary of the contributions of the thesis and a discussion of the type-based approach to knowledge representation, as well as a number of avenues for future work in this area

Natural Language Generation as an Intelligent Activity (Proposal for Dissertation Research)

In this proposal, I outline a generator conceived of as part of a general intelligent agent. The generator\u27s task is to provide the overall system with the ability to use communication in language to serve its purposes, rather than to simply encode information in language. This requires that generation be viewed as a kind of goal-directed action that is planned and executed in a dynamically changing environment. In addition, the generator must not be dependent on domain or problem-specific information but rather on a general knowledge base .that it shares with the overall system. These requirements have specific consequences for the design of the generator and the representation it uses. In particular, the text planner and the low-level linguistic component must be able to interact and negotiate over decisions that involve both high-level and low-level constraints. Also, the knowledge representation must allow for the varying perspective that an intelligent agent will have on the things it talks about; the generator must be able to appropriately vary how it describes things as the system\u27s perspective on them changes. The generator described here will demonstrate how these ideas work in practice and develop them further

A Lightweight Defeasible Description Logic in Depth: Quantification in Rational Reasoning and Beyond

Description Logics (DLs) are increasingly successful knowledge representation formalisms, useful for any application requiring implicit derivation of knowledge from explicitly known facts. A prominent example domain benefiting from these formalisms since the 1990s is the biomedical field. This area contributes an intangible amount of facts and relations between low- and high-level concepts such as the constitution of cells or interactions between studied illnesses, their symptoms and remedies. DLs are well-suited for handling large formal knowledge repositories and computing inferable coherences throughout such data, relying on their well-founded first-order semantics. In particular, DLs of reduced expressivity have proven a tremendous worth for handling large ontologies due to their computational tractability. In spite of these assets and prevailing influence, classical DLs are not well-suited to adequately model some of the most intuitive forms of reasoning. The capability for abductive reasoning is imperative for any field subjected to incomplete knowledge and the motivation to complete it with typical expectations. When such default expectations receive contradicting evidence, an abductive formalism is able to retract previously drawn, conflicting conclusions. Common examples often include human reasoning or a default characterisation of properties in biology, such as the normal arrangement of organs in the human body. Treatment of such defeasible knowledge must be aware of exceptional cases - such as a human suffering from the congenital condition situs inversus - and therefore accommodate for the ability to retract defeasible conclusions in a non-monotonic fashion. Specifically tailored non-monotonic semantics have been continuously investigated for DLs in the past 30 years. A particularly promising approach, is rooted in the research by Kraus, Lehmann and Magidor for preferential (propositional) logics and Rational Closure (RC). The biggest advantages of RC are its well-behaviour in terms of formal inference postulates and the efficient computation of defeasible entailments, by relying on a tractable reduction to classical reasoning in the underlying formalism. A major contribution of this work is a reorganisation of the core of this reasoning method, into an abstract framework formalisation. This framework is then easily instantiated to provide the reduction method for RC in DLs as well as more advanced closure operators, such as Relevant or Lexicographic Closure. In spite of their practical aptitude, we discovered that all reduction approaches fail to provide any defeasible conclusions for elements that only occur in the relational neighbourhood of the inspected elements. More explicitly, a distinguishing advantage of DLs over propositional logic is the capability to model binary relations and describe aspects of a related concept in terms of existential and universal quantification. Previous approaches to RC (and more advanced closures) are not able to derive typical behaviour for the concepts that occur within such quantification. The main contribution of this work is to introduce stronger semantics for the lightweight DL EL_bot with the capability to infer the expected entailments, while maintaining a close relation to the reduction method. We achieve this by introducing a new kind of first-order interpretation that allocates defeasible information on its elements directly. This allows to compare the level of typicality of such interpretations in terms of defeasible information satisfied at elements in the relational neighbourhood. A typicality preference relation then provides the means to single out those sets of models with maximal typicality. Based on this notion, we introduce two types of nested rational semantics, a sceptical and a selective variant, each capable of deriving the missing entailments under RC for arbitrarily nested quantified concepts. As a proof of versatility for our new semantics, we also show that the stronger Relevant Closure, can be imbued with typical information in the successors of binary relations. An extensive investigation into the computational complexity of our new semantics shows that the sceptical nested variant comes at considerable additional effort, while the selective semantics reside in the complexity of classical reasoning in the underlying DL, which remains tractable in our case

Uma proposta de interdisciplinaridade entre arquitetura da informação e ciência da computação : linguagem “SOWL” para as ontologias da Web utilizando o formalismo dos grafos conceituais

Tese (doutorado)—Universidade de Brasília, Faculdade de Ciência da Informação, 2013.A Web Semântica, sendo a nova visão proposta pelo World Wide Web Consortium (W3C) para a estrutura atual da Web, é destinada a aumentar as possibilidades que ela oferece e, dessa forma, tornar seus recursos mais acessíveis para as máquinas. Entretanto, as técnicas de raciocínio de inferência utilizadas atualmente sobre os conhecimentos descritos pelas linguagens de representação de semânticas Web se baseiam somente sobre as capacidades inferenciais do formalismo de lógicas de descrição e os da lógica de predicados, já largamente utilizados nos motores de inferências. Este fato introduz a importância das pesquisas que tratam da representação do conhecimento e das técnicas de raciocínio sobre as ontologias na ótica da Web Semântica. O presente trabalho se propõe a estudar a capacidade dos grafos conceituais para representar e operacionalizar as ontologias da Web, assim como as contribuições dessa abordagem, de um ponto de vista simbólico (poder e facilidade de representação e interpretação) e inferencial (tipos de inferência aplicáveis a esse formalismo). Sendo a Arquitetura da Informação uma disciplina indissociavelmente ligada às tecnologias da informação, o presente trabalho é uma proposta para a interdisciplinaridade entre esta e a Ciência da Computação. _______________________________________________________________________________________ ABSTRACTThe Semantic Web, being the new vision proposed by World Wide Web Consortium (W3C), to the current structure of the Web, is designed to increase the possibilities that it provides, and thereby, render its resources more accessible to machines. However, the techniques of inference on the knowledge described by representation languages of Semantic Web are based only on the inferential on formalism of description logics capabilities and formalisms of predicate logic, already widely used in the inferences engines. This fact introduces the importance of research that deals with the knowledge representation and reasoning techniques on ontologies from the perspective of the Semantic Web. The present work was geared towards the capacity of conceptual graphs to represent and operationalize the Web ontologies, as well as the contributions of this approach, as a symbolic viewpoint (power and representation, and interpretation facility) and inferential (inference types applicable to this formalism). Since the Information Architecture is one discipline inextricably linked to information tecnology, the present work is a proposal for the interdisciplinarity between this and Computer Science