Search (17 results, page 1 of 1)

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Abstract

Purpose The purpose of this paper is to identify the concepts, component parts and relationships between vocabularies, linked data and knowledge graphs (KGs) from the perspectives of data and knowledge transitions. Design/methodology/approach This paper uses conceptual analysis methods. This study focuses on distinguishing concepts and analyzing composition and intercorrelations to explore data and knowledge transitions. Findings Vocabularies are the cornerstone for accurately building understanding of the meaning of data. Vocabularies provide for a data-sharing model and play an important role in supporting the semantic expression of linked data and defining the schema layer; they are also used for entity recognition, alignment and linkage for KGs. KGs, which consist of a schema layer and a data layer, are presented as cubes that organically combine vocabularies, linked data and big data. Originality/value This paper first describes the composition of vocabularies, linked data and KGs. More importantly, this paper innovatively analyzes and summarizes the interrelatedness of these factors, which comes from frequent interactions between data and knowledge. The three factors empower each other and can ultimately empower the Semantic Web.

Date

22. 1.2021 14:24:32

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Abstract

Discusses the apparently unattainable goal of compatibility of information languages. While controlled languages can improve retrieval performance within a single system, they make cooperation across different systems more difficult. The Internet and downloading accentuate this adverse outcome and the acceleration of data exchange aggravates the problem of compatibility. Defines this familiar concept and demonstrates that coherence is just as necessary as it was for indexing languages, the proliferation of which has created confusion in grouped data banks. Describes 2 types of potential solutions, similar to those applied to automatic translation of natural languages: - harmonizing the information languages themselves, both difficult and expensive, or, the more flexible solution involving automatic harmonization of indexing formulae based on pre established concordance tables. However, structural incompatibilities between post coordinated languages and classifications may lead any harmonization tools up a blind alley, while the paths of a universal concordance model are rare and narrow

Date

1. 8.1996 22:01:00

Footnote

Übers. d. Titels: Integration of information data banks and compatibility of indexing languages

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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

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Abstract

This article deals with the meaningful processing of information in relation to two systems of Information processing: pre-coordination and post-coordination. The different approaches are discussed, with emphasis an the need for a controlled vocabulary in information retrieval. Assigned indexing, which employs a controlled vocabulary, is described in detail. Types of indexing language can be divided into two broad groups - those using pre-coordinated terms and those depending an post-coordination. They represent two different basic approaches in processing and Information retrieval. The historical development of these two approaches is described, as well as the two tools that apply to these approaches: thesauri and subject headings.

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Date

8.10.2000 11:52:22

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Date

31. 7.2006 14:22:21

Source

Cataloging and classification quarterly. 22(1996) no.1, S.77-93

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Abstract

Contemporary research in information science has concentrated on the development of methods for the algorithmic processing of natural language texts. Often, the equivalence of this approach to the intellectual technique of content analysis and indexing is claimed. It is, however, disregarded that contemporary intellectual techniques are far from exploiting their full capabilities. This is largely due to the omission of vocabulary categorisation. It is demonstrated how categorisation can drastically improve the quality of indexing and classification, and, hence, of retrieval

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Pages

S.11-22

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Abstract

Extracting semantic relationships between entities from text documents is challenging in information extraction and important for deep information processing and management. This paper investigates the incorporation of diverse lexical, syntactic and semantic knowledge in feature-based relation extraction using support vector machines. Our study illustrates that the base phrase chunking information is very effective for relation extraction and contributes to most of the performance improvement from syntactic aspect while current commonly used features from full parsing give limited further enhancement. This suggests that most of useful information in full parse trees for relation extraction is shallow and can be captured by chunking. This indicates that a cheap and robust solution in relation extraction can be achieved without decreasing too much in performance. We also demonstrate how semantic information such as WordNet, can be used in feature-based relation extraction to further improve the performance. Evaluation on the ACE benchmark corpora shows that effective incorporation of diverse features enables our system outperform previously best-reported systems. It also shows that our feature-based system significantly outperforms tree kernel-based systems. This suggests that current tree kernels fail to effectively explore structured syntactic information in relation extraction.

Source

Information processing and management. 43(2007) no.4, S.969-982

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Content

Enthält die Beiträge: SCHMITZ-ESSER, W.: Language of general communication and concept compatibility; RIESTHUIS, G.: Theory of compatibility of information languages; DAHLBERG, I.: The compatibility guidelines - a re-evaluation; SOERGEL, D.: Data structure and software support for integrated thesauri; MURASZKIEWICZ, M., H. RYBINSKI u. W. STRUK: Software problems of merging multilingual thesauri; CHMIELEWSKA-GORCZYCA, E.: Compatibility of indexing tools in multidatabase environment; NEGRINI, G.: Towards structural compatibility between concept systems; SCIBOR, E.: Some remarks on the establishment of concordances between a universal classification system and an interdisciplinary thesaurus; HOPPE, S.: The UMLS - a model for knowledge integration in a subject field; DEXTRE-CLARKE, S.: Integrating thesauri in the agricultural sciences; ROULIN, C.: Bringing multilingual thesauri together: a feasibility study; ZIMMERMANN, H.: Conception and application possibilities of classification concordances in an OPAC environment; SOSINSKA-KALATA, B.: The Universal Decimal Classification as an international standard for knowledge organization in bibliographic databases and library catalogues; WOZNIAK, J. u. T. GLOWACKA: KABA Subject Authority File - an example of an integrated Polish-French-English subject headings system; BABIK, W.: Terminology as a level for the compatibility of indexing languages - some remarks; STANCIKOVA, P.: International integrated database systems linked to multilingual thesauri covering the field of environment and agriculture; SAMEK, T.: Indexing languages integration and the EUROVOC Thesaurus in the Czech Republic; SIWEK, K.: Compatibility discrepancies between Polish and foreign databases; GLINSKI, W. u. M. MURASZKIEWICZ: An intelligent front-end processor for accessing information systems

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Content

The paper describes current work on the generation of a thesaurus format from the schedules of the Bliss Bibliographic Classification 2nd edition (BC2). The practical problems that occur in moving from a concept based approach to a terminological approach cluster around issues of vocabulary control that are not fully addressed in a systematic structure. These difficulties can be exacerbated within domains in the humanities because large numbers of culture specific terms may need to be accommodated in any thesaurus. The ways in which these problems can be resolved within the context of a semi-automated approach to the thesaurus generation have consequences for the management of classification data in the source vocabulary. The way in which the vocabulary is marked up for the purpose of machine manipulation is described, and some of the implications for editorial policy are discussed and examples given. The value of the classification notation as a language independent representation and mapping tool should not be sacrificed in such an exercise.

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Date

1. 8.1996 22:01:00

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Date

22. 9.2007 15:45:57

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Source

Wissensspeicher in digitalen Räumen: Nachhaltigkeit - Verfügbarkeit - semantische Interoperabilität. Proceedings der 11. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Konstanz, 20. bis 22. Februar 2008. Hrsg.: J. Sieglerschmidt u. H.P.Ohly

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Abstract

Natural text phrasing is an indeterminate process and, thus, inherently lacks representational predictability. This holds true in particular in the Gase of general concepts and of their syntactical connectivity. Hence, natural language query phrasing and searching is an unending adventure of trial and error and, in most Gases, has an unsatisfactory outcome with respect to the recall and precision ratlos of the responses. Human indexing is based an knowledgeable document interpretation and aims - among other things - at introducing predictability into the representation of documents. Due to the indeterminacy of natural language text phrasing and image construction, any adequate indexing is also indeterminate in nature and therefore inherently defies any satisfactory algorithmization. But human indexing suffers from a different Set of deficiencies which are absent in the processing of non-interpreted natural language. An optimally effective information System combines both types of language in such a manner that their specific strengths are preserved and their weaknesses are avoided. lf the goal is a large and enduring information system for more than merely known-item searches, the expenditure for an advanced index language and its knowledgeable and careful employment is unavoidable.

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Abstract

Linguists in the structuralist tradition (e.g., Lyons, 1977; Saussure, 1959) have asserted that concepts cannot be defined on their own but only in relation to other concepts. Semantic relations appear to reflect a logical structure in the fundamental nature of thought (Caplan & Herrmann, 1993). Green, Bean, and Myaeng (2002) noted that semantic relations play a critical role in how we represent knowledge psychologically, linguistically, and computationally, and that many systems of knowledge representation start with a basic distinction between entities and relations. Green (2001, p. 3) said that "relationships are involved as we combine simple entities to form more complex entities, as we compare entities, as we group entities, as one entity performs a process on another entity, and so forth. Indeed, many things that we might initially regard as basic and elemental are revealed upon further examination to involve internal structure, or in other words, internal relationships." Concepts and relations are often expressed in language and text. Language is used not just for communicating concepts and relations, but also for representing, storing, and reasoning with concepts and relations. We shall examine the nature of semantic relations from a linguistic and psychological perspective, with an emphasis on relations expressed in text. The usefulness of semantic relations in information science, especially in ontology construction, information extraction, information retrieval, question-answering, and text summarization is discussed. Research and development in information science have focused on concepts and terms, but the focus will increasingly shift to the identification, processing, and management of relations to achieve greater effectiveness and refinement in information science techniques. Previous chapters in ARIST on natural language processing (Chowdhury, 2003), text mining (Trybula, 1999), information retrieval and the philosophy of language (Blair, 2003), and query expansion (Efthimiadis, 1996) provide a background for this discussion, as semantic relations are an important part of these applications.

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Footnote

Original in: Information retrieval today: papers presented at an Institute conducted by the Library School and the Center for Continuation Study, University of Minnesota, Sept. 19-22, 1962. Ed. by Wesley Simonton. Minneapolis, Minn.: The Center, 1963. S.21-36.