Search (12 results, page 1 of 1)

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Abstract

More and more information is available on-line every day. The greater the amount of on-line information, the greater the demand for tools that process and disseminate this information. Processing electronic information in the form of text and answering users' queries about that information intelligently is one of the great challenges in natural language processing and information retrieval. The research presented in this talk is centered on the latter of these two tasks: intelligent information retrieval. In order for information to be retrieved, it first needs to be formalized in a database or knowledge base. The ontology for this formalization and assumptions it is based on are crucial to successful intelligent information retrieval. We have concentrated our effort on developing an ontology for representing knowledge in the domains of experimental sciences, molecular biology in particular. We show that existing ontological models cannot be readily applied to represent this domain adequately. For example, the fundamental notion of ontology design that every "real" object is defined as an instance of a category seems incompatible with the universe where objects can change their category as a result of experimental procedures. Another important problem is representing complex structures such as DNA, mixtures, populations of molecules, etc., that are very common in molecular biology. We present extensions that need to be made to an ontology to cover these issues: the representation of transformations that change the structure and/or category of their participants, and the component relations and spatial structures of complex objects. We demonstrate examples of how the proposed representations can be used to improve the quality and completeness of answers to user queries; discuss techniques for evaluating ontologies and show a prototype of an Information Retrieval System that we developed.

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Abstract

Describes the types of representations used in different theories of abstractions. Shows how the type of mapping between these representations has been increasingly generalised. Discusses desirable properties preserved by such mappings and identifies how these properties are influenced by the mappings and the presentations defined. Surveys programs made in understanding the complexity reduction associated with abstraction. Focuses on formal models of how abstraction reduces the search space. Presents some of the systems that implement abstraction. shows how the efforts in this area have focused on the mechanisation of languages for the declarative representation of abstraction.

Date

1.10.2018 14:13:22

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Abstract

The term "facet" was introduced into the field of library classification systems by Ranganathan in the 1930's [Ranganathan, 1962]. A facet is a viewpoint or aspect. In contrast to traditional classification systems, faceted systems are modular in that a domain is analyzed in terms of baseline facets which are then synthesized. In this paper, the term "facet" is used in a broader meaning. Facets can describe different aspects on the same level of abstraction or the same aspect on different levels of abstraction. The notion of facets is related to database views, multicontexts and conceptual scaling in formal concept analysis [Ganter and Wille, 1999], polymorphism in object-oriented design, aspect-oriented programming, views and contexts in description logic and semantic networks. This paper presents a definition of facets in terms of faceted knowledge representation that incorporates the traditional narrower notion of facets and potentially facilitates translation between different knowledge representation formalisms. A goal of this approach is a modular, machine-aided knowledge base design mechanism. A possible application is faceted thesaurus construction for information retrieval and data mining. Reasoning complexity depends on the size of the modules (facets). A more general analysis of complexity will be left for future research.

Date

22. 1.2016 17:30:31

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Abstract

We present a deductive data model for concept-based query expansion. It is based on three abstraction levels: the conceptual, linguistic and occurrence levels. Concepts and relationships among them are represented at the conceptual level. The expression level represents natural language expressions for concepts. Each expression has one or more matching models at the occurrence level. Each model specifies the matching of the expression in database indices built in varying ways. The data model supports a concept-based query expansion and formulation tool, the ExpansionTool, for environments providing heterogeneous IR systems. Expansion is controlled by adjustable matching reliability.

Source

Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al

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Pages

S.11-22

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Abstract

Information Systems (IS) is among the most widespread terms in the Computer Science field but a well founded, widely accepted theory of IS is still missing. With the Internet publication of the FRISCO report, the IFIP task group "FRamework of Information System COncepts" has taken a first step towards such a theory. Among the major achievements of this report are: (1) it builds on a solid basis formed by semiotics and ontology, (2) it defines a compendium of about 100 core IS concepts in a coherent and consistent way, (3) it goes beyond the common narrow view of information systems as pure technical artefacts by adopting an interdisciplinary, socio-technical view on them. In the autumn of 1999, a first review of the report and its impact was undertaken at the ISCO-4 conference in Leiden. In a workshop specifically devoted to the subject, the original aims and goals of FRISCO were confirmed to be still valid and the overall approach and achievements of the report were acknowledged. On the other hand, the workshop revealed some misconceptions, errors and weaknesses of the report in its present form, which are to be removed through a comprehensive revision now under way. This paper reports on the results of the Leiden conference and the current revision activities. It also points out some important consequences of the FRISCO approach as a whole.

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Date

22. 1.2016 17:30:31

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Abstract

Presents a proposal for the long-range development of an open, multifunctional, multilingual system for integrated access to many kinds of knowledge about concepts and terminology. The system would draw on existing knowledge bases that are accessible through the Internet or on CD-ROM and on a common integrated distributed knowledge base that would grow incrementally over time. Existing knowledge bases would be accessed througha common interface that would search several knowledge bases, collate the data into a common format, and present them to the user. The common integrated distributed knowldge base would provide an environment in which many contributors could carry out classification and terminological projects more efficiently, with the results available in a common format. Over time, data from other knowledge bases could be incorporated into the common knowledge base, either by actual transfer (provided the knowledge base producers are willing) or by reference through a link. Either way, such incorporation requires intellectual work but allows for tighter integration than common interface access to multiple knowledge bases. Each piece of information in the common knowledge base will have all its sources attached, providing an acknowledgment mechanism that gives due credit to all contributors. The whole system would be designed to be usable by many levels of users for improved information exchange.

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Abstract

This paper presents a proposal for the long-range development of an open, multifunctional, multilingual system for integrated access to many kinds of knowledge about concepts and terminology. The system would draw on existing knowledge bases that are accessible through the Internet or on CD-ROM an on a common integrated distributed knowledge base that would grow incrementally over time. Existing knowledge bases would be accessed through a common interface that would search several knowledge bases, collate the data into a common format, and present them to the user. The common integrated distributed knowledge base would provide an environment in which many contributors could carry out classification and terminological projects more efficiently, with the results available in a common format. Over time, data from other knowledge bases could be incorporated into the common knowledge base, either by actual transfer (provided the knowledge base producers are willing) or by reference through a link. Either way, such incorporation requires intellectual work but allows for tighter integration than common interface access to multiple knowledge bases. Each piece of information in the common knowledge base will have all its sources attached, providing an acknowledgment mechanism that gives due credit to all contributors. The whole system woul be designed to be usable by many levels of users for improved information exchange.

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Abstract

The ISO 2788 guidelines for monolingual thesauri contain a differentiation of "the hierarchical relationship" into "generic", "partitive", and "instance", which, for purposes of document retrieval, was deemed adequate. However, ontologies, designed as language inventories for a wider scope of knowledge representation, are based on all these and some more logical differentiations. Rereading the ISO 2788 standard and inspecting the published Cyc Upper Ontology, it is argued that the adoption of the document-retrieval definition of subsumption generally prevents the conception or use of a thesaurus as a substructure of an ontology of the new kind as constructed for AI applications. When a thesaurus is used for fact description and inference on fact descriptions, the instance-of relationship too should be reconsidered: It may also link concepts and metaconcepts, and then its distinction from subsumption is needed. The treatment of the instance-of relationship in thesauri, the Cyc Upper Ontology, and WordNet is described from this perspective

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Abstract

The aim of this book is to highlight the relationship between knowledge representation and language in artificial intelligence, and in particular on the way in which the choice of representation influences the language used to discuss a problem - and vice versa. Opening with a discussion of knowledge representation methods, and following this with a look at reasoning methods, the author begins to make his case for the intimate relationship between language and representation. He shows how each representation method fits particularly well with some reasoning methods and less so with others, using specific languages as examples. The question of representation change, an important and complex issue about which very little is known, is addressed. Dr Hodgson gathers together recent work on problem solving, showing how, in some cases, it has been possible to use representation changes to recast problems into a language that makes them easier to solve. The author maintains throughout that the relationships that this book explores lie at the heart of the construction of large systems, examining a number of the current large AI systems from the viewpoint of representation and language to prove his point.

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Content

G. Gainotti, M.C. Silveri, A. Daniele, L. Giustolisi, Neuroanatomical Correlates of Category-specific Semantic Disorders: A Critical Survey. J. S. Snowden, H. L. Griffiths, D. Neary, Autobiographical Experience and Word Meaning. L. Cipolotti, E.K. Warrington, Towards a Unitary Account of Access Dysphasia: A Single Case Study. E. Forde, G.W. Humphreys, Refractory Semantics in Global Aphasia: On Semantic Organisation and the Access-Storage Distinction in Neuropsychology. A. E. Hillis, A. Caramazza, The Compositionality of Lexical Semantic Representations: Clues from Semantic Errors in Object Naming. H.E. Moss, L.K. Tyler, Investigating Semantic Memory Impairments: The Contribution of Semantic Priming. K.R. Laws, S.A. Humber, D.J.C. Ramsey, R.A. McCarthy, Probing Sensory and Associative Semantics for Animals and Objects in Normal Subjects. K.R. Laws, J.J. Evans, J. R. Hodges, R.A. McCarthy, Naming without Knowing and Appearance without Associations: Evidence for Constructive Processes in Semantic Memory? J. Powell, J. Davidoff, Selective Impairments of Object-knowledge in a Case of Acquired Cortical Blindness. J.R. Hodges, N. Graham, K. Patterson, Charting the Progression in Semantic Dementia: Implications for the Organisation of Semantic Memory. E. Funnell, Objects and Properties: A Study of the Breakdown of Semantic Memory. L.J. Tippett, S. McAuliffe, M. J. Farrar, Preservation of Categorical Knowledge in Alzheimer's Disease: A Computational Account. G. W. Humphreys, C. Lamote, T.J. Lloyd-Jones, An Interactive Activation Approach to Object Processing: Effects of Structural Similarity, Name Frequency, and Task in Normality and Pathology.