-
Salton, G.: Another look at automatic text-retrieval systems (1986)
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- Footnote
- Bezugnahme auf: Blair, D.C.: An evaluation of retrieval effectiveness for a full-text document-retrieval system. Comm. ACM 28(1985) S.280-299. - Vgl. auch: Blair, D.C.: Full text retrieval ... Int. Class. 13(1986) S.18-23; Blair, D.C., M.E. Maron: full-text information retrieval ... Inf. Proc. Man. 26(1990) S.437-447.
-
Alexander, M.: Retrieving digital data with fuzzy matching (1996)
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- Abstract
- Briefly describes the Excalibur EFS system which makes use of adaptive pattern recognition technology as an aid to automatic indexing and how it is being tested at the British Library for the indexing and retrieval of scanned images from the library's holdings. Notes how Excalibur EFS can support a wide degree of fuzzy searching, compensate for the errors produced by OCR conversion of scanned images, reduce the costs of indexing, and require far less storage space than more traditional indexes
-
Bordoni, L.; Pazienza, M.T.: Documents automatic indexing in an environmental domain (1997)
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- Abstract
- Describes an application of Natural Language Processing (NLP) techniques, in HIRMA (Hypertextual Information Retrieval Managed by ARIOSTO), to the problem of document indexing by referring to a system which incorporates natural language processing techniques to determine the subject of the text of documents and to associate them with relevant semantic indexes. Describes briefly the overall system, details of its implementation on a corpus of scientific abstracts related to environmental topics and experimental evidence of the system's behaviour. Analyzes in detail an experiment designed to evaluate the system's retrieval ability in terms of recall and precision
- Source
- International forum on information and documentation. 22(1997) no.1, S.17-28
-
Dattola, R.T.: FIRST: Flexible information retrieval system for text (1979)
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- Source
- Journal of the American Society for Information Science. 30(1979), S.9-14
-
Garfield, E.; Sager, N.: Mechanical indexing, structural linguistics and information retrieval (1993)
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- Source
- Journal of information science. 19(1993) no.2, S.164-165
-
Daudaravicius, V.: ¬A framework for keyphrase extraction from scientific journals (2016)
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- Content
- Vortrag, "Semantics, Analytics, Visualisation: Enhancing Scholarly Data Workshop co-located with the 25th International World Wide Web Conference April 11, 2016 - Montreal, Canada", Montreal 2016.
-
Lepsky, K.; Vorhauer, J.: Lingo - ein open source System für die Automatische Indexierung deutschsprachiger Dokumente (2006)
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- Abstract
- Lingo ist ein frei verfügbares System (open source) zur automatischen Indexierung der deutschen Sprache. Bei der Entwicklung von lingo standen hohe Konfigurierbarkeit und Flexibilität des Systems für unterschiedliche Einsatzmöglichkeiten im Vordergrund. Der Beitrag zeigt den Nutzen einer linguistisch basierten automatischen Indexierung für das Information Retrieval auf. Die für eine Retrievalverbesserung zur Verfügung stehende linguistische Funktionalität von lingo wird vorgestellt und an Beispielen erläutert: Grundformerkennung, Kompositumerkennung bzw. Kompositumzerlegung, Wortrelationierung, lexikalische und algorithmische Mehrwortgruppenerkennung, OCR-Fehlerkorrektur. Der offene Systemaufbau von lingo wird beschrieben, mögliche Einsatzszenarien und Anwendungsgrenzen werden benannt.
- Date
- 24. 3.2006 12:22:02
-
Gray, W.A.; Harley, A.J.: Computer assisted indexing (1971)
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- Source
- Information storage and retrieval. 7(1971), S.167-174
-
Stiles, H.E.: ¬The association factor in information retrieval (1961)
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-
Sparck Jones, K.: Index term weighting (1973)
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- Source
- Information storage and retrieval. 9(1973), S.619-633
-
Fuhr, N.; Knorz, G.: Retrieval test evaluation of a rule based automatic indexing (AIR/PHYS) (1984)
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- Source
- Research and development in information retrieval. Proc. of the 3rd joint BCS and ACM symp., Cambridge, 2.-6.7.1984. Ed.: C.J. van Rijsbergen
-
Griffiths, A.; Luckhurst, H.C.; Willett, P.: Using interdocument similarity information in document retrieval systems (1986)
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- Source
- Journal of the American Society for Information Science. 37(1986) no.1, S.3-11
-
Wan, T.-L.; Evens, M.; Wan, Y.-W.; Pao, Y.-Y.: Experiments with automatic indexing and a relational thesaurus in a Chinese information retrieval system (1997)
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- Abstract
- This article describes a series of experiments with an interactive Chinese information retrieval system named CIRS and an interactive relational thesaurus. 2 important issues have been explored: whether thesauri enhance the retrieval effectiveness of Chinese documents, and whether automatic indexing can complete with manual indexing in a Chinese information retrieval system. Recall and precision are used to measure and evaluate the effectiveness of the system. Statistical analysis of the recall and precision measures suggest that the use of the relational thesaurus does improve the retrieval effectiveness both in the automatic indexing environment and in the manual indexing environment and that automatic indexing is at least as good as manual indexing
- Source
- Journal of the American Society for Information Science. 48(1997) no.12, S.1086-1096
-
Flores, F.N.; Moreira, V.P.: Assessing the impact of stemming accuracy on information retrieval : a multilingual perspective (2016)
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- Abstract
- The quality of stemming algorithms is typically measured in two different ways: (i) how accurately they map the variant forms of a word to the same stem; or (ii) how much improvement they bring to Information Retrieval systems. In this article, we evaluate various stemming algorithms, in four languages, in terms of accuracy and in terms of their aid to Information Retrieval. The aim is to assess whether the most accurate stemmers are also the ones that bring the biggest gain in Information Retrieval. Experiments in English, French, Portuguese, and Spanish show that this is not always the case, as stemmers with higher error rates yield better retrieval quality. As a byproduct, we also identified the most accurate stemmers and the best for Information Retrieval purposes.
- Source
- Information processing and management. 52(2016) no.5, S.840-854
-
Chowdhury, G.G.: Natural language processing and information retrieval : pt.1: basic issues; pt.2: major applications (1991)
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- Abstract
- Reviews the basic issues and procedures involved in natural language processing of textual material for final use in information retrieval. Covers: natural language processing; natural language understanding; syntactic and semantic analysis; parsing; knowledge bases and knowledge representation
-
Pritchard, J.: Information retrieval : smarter indexing (1991)
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- Abstract
- Describes full text retrieval (FTR) which indexes every occurrence of every word except defined 'stop' words. This permits much more sophisticated searching than with keyword indexing. Also discusses document imaging processing (DIP). Lists suppliers and users of the software and describes the experiences of ESOO's Planning Division with Computer Intertrade Ltd. (CIL) ImagePro DIP and their operational practices
- Source
- Advanced information report. 1991, S.7-9
-
Smiraglia, R.P.; Cai, X.: Tracking the evolution of clustering, machine learning, automatic indexing and automatic classification in knowledge organization (2017)
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- Abstract
- A very important extension of the traditional domain of knowledge organization (KO) arises from attempts to incorporate techniques devised in the computer science domain for automatic concept extraction and for grouping, categorizing, clustering and otherwise organizing knowledge using mechanical means. Four specific terms have emerged to identify the most prevalent techniques: machine learning, clustering, automatic indexing, and automatic classification. Our study presents three domain analytical case analyses in search of answers. The first case relies on citations located using the ISKO-supported "Knowledge Organization Bibliography." The second case relies on works in both Web of Science and SCOPUS. Case three applies co-word analysis and citation analysis to the contents of the papers in the present special issue. We observe scholars involved in "clustering" and "automatic classification" who share common thematic emphases. But we have found no coherence, no common activity and no social semantics. We have not found a research front, or a common teleology within the KO domain. We also have found a lively group of authors who have succeeded in submitting papers to this special issue, and their work quite interestingly aligns with the case studies we report. There is an emphasis on KO for information retrieval; there is much work on clustering (which involves conceptual points within texts) and automatic classification (which involves semantic groupings at the meta-document level).
-
Renz, M.: Automatische Inhaltserschließung im Zeichen von Wissensmanagement (2001)
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- Abstract
- Methoden der automatischen Inhaltserschließung werden seit mehr als 30 Jahren entwickelt, ohne in luD-Kreisen auf merkliche Akzeptanz zu stoßen. Gegenwärtig führen jedoch die steigende Informationsflut und der Bedarf an effizienten Zugriffsverfahren im Informations- und Wissensmanagement in breiten Anwenderkreisen zu einem wachsenden Interesse an diesen Methoden, zu verstärkten Anstrengungen in Forschung und Entwicklung und zu neuen Produkten. In diesem Beitrag werden verschiedene Ansätze zu intelligentem und inhaltsbasiertem Retrieval und zur automatischen Inhaltserschließung diskutiert sowie kommerziell vertriebene Softwarewerkzeuge und Lösungen präsentiert. Abschließend wird festgestellt, dass in naher Zukunft mit einer zunehmenden Automatisierung von bestimmten Komponenten des Informations- und Wissensmanagements zu rechnen ist, indem Software-Werkzeuge zur automatischen Inhaltserschließung in den Workflow integriert werden
- Date
- 22. 3.2001 13:14:48
- Source
- nfd Information - Wissenschaft und Praxis. 52(2001) H.2, S.69-78
-
Pfeifer, U.: Entwicklung linear-iterativer und logistischer Indexierungsfunktionen (1991)
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- Source
- Information retrieval: GI/GMD-Workshop, Darmstadt, 23.-24.6.1991: Proceedings. Ed.: N. Fuhr
-
Panyr, J.: Vektorraum-Modell und Clusteranalyse in Information-Retrieval-Systemen (1987)
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- Abstract
- Ausgehend von theoretischen Indexierungsansätzen wird das klassische Vektorraum-Modell für automatische Indexierung (mit dem Trennschärfen-Modell) erläutert. Das Clustering in Information-Retrieval-Systemem wird als eine natürliche logische Folge aus diesem Modell aufgefaßt und in allen seinen Ausprägungen (d.h. als Dokumenten-, Term- oder Dokumenten- und Termklassifikation) behandelt. Anschließend werden die Suchstrategien in vorklassifizierten Dokumentenbeständen (Clustersuche) detailliert beschrieben. Zum Schluß wird noch die sinnvolle Anwendung der Clusteranalyse in Information-Retrieval-Systemen kurz diskutiert
