Search (34 results, page 2 of 2)

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Abstract

Automatic identification of semantic relations in text is a difficult problem, but is important for many applications. It has been used for relation matching in information retrieval to retrieve documents that contain not only the concepts but also the relations between concepts specified in the user's query. It is an integral part of information extraction-extracting from natural language text, facts or pieces of information related to a particular event or topic. Other potential applications are in the construction of relational thesauri (semantic networks of related concepts) and other kinds of knowledge bases, and in natural language processing applications such as machine translation and computer comprehension of text. This chapter examines the main methods used for identifying semantic relations automatically and their application in information retrieval and information extraction.

Type

a

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Abstract

Thesaural relations have long been used in information retrieval to enrich queries; they have sometimes been used to cluster documents as well. Sometimes the first query to an information retrieval system yields no results at all, or, what can be even more disconcerting, many thousands of hits. One solution is to rephrase the query, improving the choice of query terms by using related terms of different types. A collection of related terms is often called a thesaurus. This chapter describes the lexical-semantic relations that have been used in building thesauri and summarizes some of the effects of using these relational thesauri in information retrieval experiments

Type

a

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Abstract

The Internet is a giant semiotic system. It is a massive collection of Peirce's three kinds of signs: icons, which show the form of something; indices, which point to something; and symbols, which represent something according to some convention. But current proposals for ontologies and metadata have overlooked some of the most important features of signs. A sign has three aspects: it is (1) an entity that represents (2) another entity to (3) an agent. By looking only at the signs themselves, some metadata proposals have lost sight of the entities they represent and the agents - human, animal, or robot - which interpret them. With its three branches of syntax, semantics, and pragmatics, semiotics provides guidelines for organizing and using signs to represent something to someone for some purpose. Besides representation, semiotics also supports methods for translating patterns of signs intended for one purpose to other patterns intended for different but related purposes. This article shows how the fundamental semiotic primitives are represented in semantically equivalent notations for logic, including controlled natural languages and various computer languages

Type

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Abstract

This paper deals with different views of lexical semantics. The focus is on the relationship between lexical expressions and conceptual components. First the assumptions about lexicalization and decompositionality of concepts shared by the most semanticists are presented, followed by a discussion of the differences between two-level-semants and one-level-semantics. The final part is concentrated on the interpretation of conceptual components in situations of communication

Type

a

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Abstract

Work on relationships takes place in many communities, including, among others, data modeling, knowledge representation, natural language processing, linguistics, and information retrieval. Unfortunately, continued disciplinary splintering and specialization keeps any one person from being familiar with the full expanse of that work. By including contributions form experts in a variety of disciplines and backgrounds, this volume demonstrates both the parallels that inform work on relationships across a number of fields and the singular emphases that have yet to be fully embraced, The volume is organized into 3 parts: (1) Types of relationships (2) Relationships in knowledge representation and reasoning (3) Applications of relationships

Content

Enthält die Beiträge: Pt.1: Types of relationships: CRUDE, D.A.: Hyponymy and its varieties; FELLBAUM, C.: On the semantics of troponymy; PRIBBENOW, S.: Meronymic relationships: from classical mereology to complex part-whole relations; KHOO, C. u.a.: The many facets of cause-effect relation - Pt.2: Relationships in knowledge representation and reasoning: GREEN, R.: Internally-structured conceptual models in cognitive semantics; HOVY, E.: Comparing sets of semantic relations in ontologies; GUARINO, N., C. WELTY: Identity and subsumption; JOUIS; C.: Logic of relationships - Pt.3: Applications of relationships: EVENS, M.: Thesaural relations in information retrieval; KHOO, C., S.H. MYAENG: Identifying semantic relations in text for information retrieval and information extraction; McCRAY, A.T., O. BODENREICHER: A conceptual framework for the biiomedical domain; HETZLER, B.: Visual analysis and exploration of relationships

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Abstract

Concept theory is an extremely broad, interdisciplinary and complex field of research related to many deep fields with very long historical traditions without much consensus. However, information science and knowledge organization cannot avoid relating to theories of concepts. Knowledge organizing systems (e.g., classification systems, thesauri, and ontologies) should be understood as systems basically organizing concepts and their semantic relations. The same is the case with information retrieval systems. Different theories of concepts have different implications for how to construe, evaluate, and use such systems. Based on a post-Kuhnian view of paradigms, this article put forward arguments that the best understanding and classification of theories of concepts is to view and classify them in accordance with epistemological theories (empiricism, rationalism, historicism, and pragmatism). It is also argued that the historicist and pragmatist understandings of concepts are the most fruitful views and that this understanding may be part of a broader paradigm shift that is also beginning to take place in information science. The importance of historicist and pragmatic theories of concepts for information science is outlined.

Type

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Abstract

Meronymic or partonomic relations are ontological relations that are considered as fundamental as the ubiquitous, taxonomic subsumption relationship. While the latter is well-established and thoroughly investigated, there is still much work to be done in the field of meronymic relations. The aim of this chapter is to provide an overview an current research in characterizing, formalizing, classifying, and processing meronymic or partonomic relations (also called part-whole relations in artificial intelligence and application domains). The first part of the chapter investigates the role of knowledge about parts in human cognition, for example, visual perception and conceptual knowledge. The second part describes the classical approach provided by formal mereology and its extensions, which use one single transitive part-of relation, thus focusing an the notion of "part" and neglecting the notion of (something being a) "whole". This limitation leads to classifications of different part-whole relations, one of which is presented in the last part of the chapter.

Type

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Abstract

Ontologie ist in der Philosophie die Auseinandersetzung mit der Frage, welche Arten von Gegenständen existieren und in welcher Weise sie existieren. Ein zentrales Thema ist z. B., ob es geistige Gegenstände, z. B. Gedanken, Ideen, Begriffe, Vorstellungen u. a. gibt und wie ihre Existenz begründet wird. Neuerdings wird mit dem Wort "Ontologie" eine andere, etwas konkretere Bedeutung verbunden. Unter einer Ontologie werden die allgemeinsten Begriffe eines Fachgebiets verstanden. So gehören zur Ontologie des Organischen u. a. "Pflanze", "Tier" und "Mensch". Wenn der Begriff "Tier" schon gegeben ist, lassen sich daraus andere Begriffe, z. B. "Wirbeltier", "Reptil", "Säugetier" usw. spezifizierend durch Angabe weiterer Merkmale bilden. Außerdem können Begriffsbeziehungen und andere formale Mittel zu Ontologien gehören. Ontologie ist danach die Methode, durch die die Begriffswelt eines Sachgebiets bestimmt wird, und insbesondere das Ergebnis dieser Methode: die Struktur aus Begriffen höchster Allgemeinheit, die mit dieser Methode erstellt wird. Das Wort "Ontologie" kann jedoch unterschiedlich verstanden wird. Es bezeichnet auch die Gesamtheit aller Begriffe, die zum Untersuchungsgegenstand gehören. Die Ontologie umfasst dann alles, was an Begriffen aus einer bestimmten Aufgabenstellung betrachtet bzw. erarbeitet wird. Zu einer Ontologie der Elektronik würden alle Begriffe dieses Gebietes gehören. Mit einem so weit gefassten Verständnis des Wortes "Ontologie" wird die Fokussierung auf die Kategorien größter Allgemeinheit der hierarchisch gegliederten Begriffswelt aufgegeben. Außerdem würde eine so verstandene Ontologie mit der Tatsache der Unabgrenzbarkeit des Wortschatzes belastet werden. Komposita können im Deutschen quasi unbegrenzt erweitert werden. Es gibt nicht nur den Kamin und den Kaminfeger, sondern auch die Kaminfegerarbeitskleidungsreinigungsfirma und dergleichen mehr. Komposita sind unverzichtbar. Ihre maximale Länge ist nicht festgelegt. Die Benennungen für Stoffe in der Chemie zeigen, dass man in dieser Fachsprache durchaus problemlos mit sehr langen Zusammensetzungen kommuniziert. Aber die Ontologen werden nicht daran interessiert sein, ihre Untersuchungen bis in die Tiefen aller Fachgebiete auszudehnen. Kurzum "Ontologie" sollte sich auf Begriffe höchster Allgemeinheit beziehen. Das entspricht der engeren Bedeutung des Wortes "Ontologie". Die Unterbegriffe dieser Top-Level-Begriffe können natürlich ebenfalls für Ontologen von Interesse sein, weil sie zeigen, welches Begriffsbildungspotenzial die verschiedenen Top-Level-Begriffe haben. Der Schwerpunkt des Interesses der Ontologen sollte aber auf den Begriffen liegen, die nicht weiter zurückführbar sind.

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