Search (338 results, page 1 of 17)

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LCSH

FERRET (Information retrieval system)
Information storage and retrieval

RSWK

Freitextsuche / Information Retrieval
Information Retrieval / Expertensystem
Syntaktische Analyse Information Retrieval

Subject

Freitextsuche / Information Retrieval
Information Retrieval / Expertensystem
Syntaktische Analyse Information Retrieval
FERRET (Information retrieval system)
Information storage and retrieval

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Series

The Kluwer International series on information retrieval

Source

Cross-language information retrieval. Ed.: G. Grefenstette

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Source

Encyclopedia of library and information science. Vol.55, [=Suppl.18]

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Source

Journal of information science. 26(2000) no.2, S.75-85

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Source

Information processing and management. 36(2000) no.1, S.155-205

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Source

Information retrieval. 4(2001), S.209-230

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Abstract

Storing and accessing texts in a conceptual format has a number of advantages over traditional document retrieval methods. A conceptual format facilitates natural language access to text information. It can support imprecise and inexact queries, conceptual information summarisation, and, ultimately, document translation. Describes 2 methods which have been implemented in a prototype intelligent information retrieval system calles SCISOR (System for Conceptual Information Summarisation, Organization and Retrieval). Describes the text processing, language acquisition, and summarisation components of SCISOR

Source

Information processing and management. 25(1989) no.4, S.419-428

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Abstract

This article explores how linguistics has influenced information retrieval (IR) and attempts to explain the impact of linguistics through an analysis of internal developments in information science generally, and IR in particular. It notes that information science/IR has been evolving from a case science into a fully fledged, "disciplined"/disciplinary science. The article establishes correspondences between linguistics and information science/IR using the three established IR paradigms-physical, cognitive, and computational-as a frame of reference. The current relationship between information science/IR and linguistics is elucidated through discussion of some recent information science publications dealing with linguistic topics and a novel technique, "keyword collocation analysis," is introduced. Insights from interdisciplinarity research and case theory are also discussed. It is demonstrated that the three stages of interdisciplinarity, namely multidisciplinarity, interdisciplinarity (in the narrow sense), and transdisciplinarity, can be linked to different phases of the information science/IR-linguistics relationship and connected to different ways of using linguistic theory in information science and IR.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.3, S.660-680

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Abstract

Linguistics is the scientific study of language which emphasizes language spoken in everyday settings by human beings. It has a long history of interdisciplinarity, both internally and in contribution to other fields, including information science. A linguistic perspective is beneficial in many ways in information science, since it examines the relationship between the forms of meaningful expressions and their social, cognitive, institutional, and communicative context, these being two perspectives on information that are actively studied, to different degrees, in information science. Examples of issues relevant to information science are presented for which the approach taken under a linguistic perspective is illustrated.

Source

Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates

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Abstract

Natural language processing (NLP) is the computerized approach to analyzing text that is based on both a set of theories and a set of technologies. Although NLP is a relatively recent area of research and application, compared with other information technology approaches, there have been sufficient successes to date that suggest that NLP-based information access technologies will continue to be a major area of research and development in information systems now and into the future.

Source

Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates

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Abstract

The constituent object parser is designed to improve the precision and recall performance of information retrieval by providing more powerful matching procedures. Describes the dependency tree representations and the relationship between the intended use of the parser and its design.

Source

ACM transactions on information systems. 7(1989) no.3, S.292-316

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Footnote

Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.440-445.

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Source

Journal of information science. 25(1999) no.2, S.113-131

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Source

Journal of information science. 26(2000) no.6, S.429-451

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Source

Journal of information science. 26(2000) no.6, S.461-467

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Abstract

Text classification (TC) is a core technique for text mining and information retrieval. It has been applied to many applications in many different research and industrial areas. Term-weighting schemes assign an appropriate weight to each term to obtain a high TC performance. Although term weighting is one of the important modules for TC and TC has different peculiarities from those in information retrieval, many term-weighting schemes used in information retrieval, such as term frequency-inverse document frequency (tf-idf), have been used in TC in the same manner. The peculiarity of TC that differs most from information retrieval is the existence of class information. This article proposes a new term-weighting scheme that uses class information using positive and negative class distributions. As a result, the proposed scheme, log tf-TRR, consistently performs better than do other schemes using class information as well as traditional schemes such as tf-idf.

Source

Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2553-2565

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Source

New trends in documentation and information. E.: P.J. Taylor

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