-
Driscoll, J.R.; Rajala, D.A.; Shaffer, W.H.: ¬The operation and performance of an artificially intelligent keywording system (1991)
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- Abstract
- Presents a new approach to text analysis for automating the key phrase indexing process, using artificial intelligence techniques. This mimics the behaviour of human experts by using a rule base consisting of insertion and deletion rules generated by subject-matter experts. The insertion rules are based on the idea that some phrases found in a text imply or trigger other phrases. The deletion rules apply to semantically ambiguous phrases where text presence alone does not determine appropriateness as a key phrase. The insertion and deletion rules are used to transform a list of found phrases to a list of key phrases for indexing a document. Statistical data are provided to demonstrate the performance of this expert rule based system
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Salton, G.: Automatic processing of foreign language documents (1985)
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- Footnote
- Original in: Journal of the American Society for Information Science 21(1970) no.3, S.187-194.
- Source
- Theory of subject analysis: a sourcebook. Ed.: L.M. Chan, et al
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Witschel, H.F.: Terminology extraction and automatic indexing : comparison and qualitative evaluation of methods (2005)
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- Abstract
- Many terminology engineering processes involve the task of automatic terminology extraction: before the terminology of a given domain can be modelled, organised or standardised, important concepts (or terms) of this domain have to be identified and fed into terminological databases. These serve in further steps as a starting point for compiling dictionaries, thesauri or maybe even terminological ontologies for the domain. For the extraction of the initial concepts, extraction methods are needed that operate on specialised language texts. On the other hand, many machine learning or information retrieval applications require automatic indexing techniques. In Machine Learning applications concerned with the automatic clustering or classification of texts, often feature vectors are needed that describe the contents of a given text briefly but meaningfully. These feature vectors typically consist of a fairly small set of index terms together with weights indicating their importance. Short but meaningful descriptions of document contents as provided by good index terms are also useful to humans: some knowledge management applications (e.g. topic maps) use them as a set of basic concepts (topics). The author believes that the tasks of terminology extraction and automatic indexing have much in common and can thus benefit from the same set of basic algorithms. It is the goal of this paper to outline some methods that may be used in both contexts, but also to find the discriminating factors between the two tasks that call for the variation of parameters or application of different techniques. The discussion of these methods will be based on statistical, syntactical and especially morphological properties of (index) terms. The paper is concluded by the presentation of some qualitative and quantitative results comparing statistical and morphological methods.
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Porter, M.F.: ¬An algorithm for suffix stripping (1980)
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- Footnote
- Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.313-316.
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Goller, C.; Löning, J.; Will, T.; Wolff, W.: Automatic document classification : a thourough evaluation of various methods (2000)
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- Date
- 17. 1.1997 17:19:26
-
Li, W.; Wong, K.-F.; Yuan, C.: Toward automatic Chinese temporal information extraction (2001)
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- Source
- Journal of the American Society for Information Science and technology. 52(2001) no.9, S.748-762
-
Fagan, J.L.: ¬The effectiveness of a nonsyntactic approach to automatic phrase indexing for document retrieval (1989)
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- Source
- Journal of the American Society for Information Science. 40(1989) no.2, S.115-132
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Fox, C.: Lexical analysis and stoplists (1992)
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- Source
- Information retrieval: data structures and algorithms. Ed.: W.B. Frakes u. R. Baeza-Yates
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Riloff, E.: ¬An empirical study of automated dictionary construction for information extraction in three domains (1996)
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- Date
- 6. 3.1997 16:22:15
-
Wacholder, N.; Byrd, R.J.: Retrieving information from full text using linguistic knowledge (1994)
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- Source
- Proceedings of the 15th National Online Meeting 1994, New York, 10-12 May 1994. Ed. by M.E. Williams
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Needham, R.M.; Sparck Jones, K.: Keywords and clumps (1985)
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- Source
- Theory of subject analysis: a sourcebook. Ed.: L.M. Chan, et al
