-
Golub, K.; Lykke, M.; Tudhope, D.: Enhancing social tagging with automated keywords from the Dewey Decimal Classification (2014)
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- Abstract
- Purpose - The purpose of this paper is to explore the potential of applying the Dewey Decimal Classification (DDC) as an established knowledge organization system (KOS) for enhancing social tagging, with the ultimate purpose of improving subject indexing and information retrieval. Design/methodology/approach - Over 11.000 Intute metadata records in politics were used. Totally, 28 politics students were each given four tasks, in which a total of 60 resources were tagged in two different configurations, one with uncontrolled social tags only and another with uncontrolled social tags as well as suggestions from a controlled vocabulary. The controlled vocabulary was DDC comprising also mappings from the Library of Congress Subject Headings. Findings - The results demonstrate the importance of controlled vocabulary suggestions for indexing and retrieval: to help produce ideas of which tags to use, to make it easier to find focus for the tagging, to ensure consistency and to increase the number of access points in retrieval. The value and usefulness of the suggestions proved to be dependent on the quality of the suggestions, both as to conceptual relevance to the user and as to appropriateness of the terminology. Originality/value - No research has investigated the enhancement of social tagging with suggestions from the DDC, an established KOS, in a user trial, comparing social tagging only and social tagging enhanced with the suggestions. This paper is a final reflection on all aspects of the study.
- Theme
- Social tagging
-
Martins, A.L.; Souza, R.R.; Ribeiro de Mello, H.: ¬The use of noun phrases in information retrieval : proposing a mechanism for automatic classification (2014)
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- Abstract
- This paper presents a research on syntactic structures known as noun phrases (NP) being applied to increase the effectiveness and efficiency of the mechanisms for the document's classification. Our hypothesis is the fact that the NP can be used instead of single words as a semantic aggregator to reduce the number of words that will be used for the classification system without losing its semantic coverage, increasing its efficiency. The experiment divided the documents classification process in three phases: a) NP preprocessing b) system training; and c) classification experiments. In the first step, a corpus of digitalized texts was submitted to a natural language processing platform1 in which the part-of-speech tagging was done, and them PERL scripts pertaining to the PALAVRAS package were used to extract the Noun Phrases. The preprocessing also involved the tasks of a) removing NP low meaning pre-modifiers, as quantifiers; b) identification of synonyms and corresponding substitution for common hyperonyms; and c) stemming of the relevant words contained in the NP, for similitude checking with other NPs. The first tests with the resulting documents have demonstrated its effectiveness. We have compared the structural similarity of the documents before and after the whole pre-processing steps of phase one. The texts maintained the consistency with the original and have kept the readability. The second phase involves submitting the modified documents to a SVM algorithm to identify clusters and classify the documents. The classification rules are to be established using a machine learning approach. Finally, tests will be conducted to check the effectiveness of the whole process.
- Source
- Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
-
Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986)
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- Source
- Information processing and management. 22(1986) no.6, S.465-476
-
Donath, A.: Flickr sorgt mit Automatik-Tags für Aufregung (2015)
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- Content
- "Flickr hat ein Tagging der heraufgeladenen Fotos eingeführt, das zusätzlich zu den Bildbeschreibungen der Nutzer versucht, die Fotos mit Schlagwörtern zu versehen, die den Bildinhalt beschreiben. Nach einem Bericht des britischen Guardian werden dabei Fehler gemacht, die unangebrachte Beschreibungen bis hin zu rassistischen oder politisch inkorrekten Bemerkungen beinhalten. So wurden dunkelhäutiger Menschen als "monochrom", "Tier" und "Affe" beschrieben. Auch das Gesicht einer hellhäutigen Frau wurde mit "Tier" klassifiziert. Bilder eines Konzentrationslagers wurden gar mit "Sport" und "Klettergerüst" verschlagwortet. Die automatischen Tags lassen sich nicht abschalten - und befinden sich nach Angaben von Yahoo noch in der Betaphase. Viel bringen sie nach Einschätzung von Golem.de nicht, da sie recht allgemein gehalten und wenig aussagekräftig sind. Oftmals kann der Algorithmus nur "Indoor" oder "Outdoor" hinzufügen, was zwar fast immer korrekt zugeordnet wird, dennoch wenig nutzt. Hinter den Kulissen scheint Flickr bereits an einer Verbesserung zu arbeiten - und hat dem Guardian auf Nachfrage versichert, dass die Probleme mit falschen Tags bekannt seien. Einige fehlerhafte Schlagwörter wurden mittlerweile auch wieder entfernt." Vgl. auch: https://news.ycombinator.com/item?id=8621658.
-
Bredack, J.: Automatische Extraktion fachterminologischer Mehrwortbegriffe : ein Verfahrensvergleich (2016)
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- Abstract
- Als Extraktionssysteme wurden der TreeTagger und die Indexierungssoftware Lingo verwendet. Der TreeTagger basiert auf einem statistischen Tagging- und Chunking- Algorithmus, mit dessen Hilfe NPs automatisch identifiziert und extrahiert werden. Er kann für verschiedene Anwendungsszenarien der natürlichen Sprachverarbeitung eingesetzt werden, in erster Linie als POS-Tagger für unterschiedliche Sprachen. Das Indexierungssystem Lingo arbeitet im Gegensatz zum TreeTagger mit elektronischen Wörterbüchern und einem musterbasierten Abgleich. Lingo ist ein auf automatische Indexierung ausgerichtetes System, was eine Vielzahl von Modulen mitliefert, die individuell auf eine bestimmte Aufgabenstellung angepasst und aufeinander abgestimmt werden können. Die unterschiedlichen Verarbeitungsweisen haben sich in den Ergebnismengen beider Systeme deutlich gezeigt. Die gering ausfallenden Übereinstimmungen der Ergebnismengen verdeutlichen die abweichende Funktionsweise und konnte mit einer qualitativen Analyse beispielhaft beschrieben werden. In der vorliegenden Arbeit kann abschließend nicht geklärt werden, welches der beiden Systeme bevorzugt für die Generierung von Indextermen eingesetzt werden sollte.
-
Fuhr, N.; Niewelt, B.: ¬Ein Retrievaltest mit automatisch indexierten Dokumenten (1984)
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- Date
- 20.10.2000 12:22:23
-
Hlava, M.M.K.: Automatic indexing : comparing rule-based and statistics-based indexing systems (2005)
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- Source
- Information outlook. 9(2005) no.8, S.22-23
-
Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986)
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- Date
- 14. 6.2015 22:12:44
-
Hauer, M.: Automatische Indexierung (2000)
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- Source
- Wissen in Aktion: Wege des Knowledge Managements. 22. Online-Tagung der DGI, Frankfurt am Main, 2.-4.5.2000. Proceedings. Hrsg.: R. Schmidt
-
Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986)
0.02
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- Date
- 14. 6.2015 22:12:56
-
Hauer, M.: Tiefenindexierung im Bibliothekskatalog : 17 Jahre intelligentCAPTURE (2019)
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- Source
- B.I.T.online. 22(2019) H.2, S.163-166
-
Carevic, Z.: Semi-automatische Verschlagwortung zur Integration externer semantischer Inhalte innerhalb einer medizinischen Kooperationsplattform (2012)
0.02
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- Abstract
- Die vorliegende Arbeit beschäftigt sich mit der Integration von externen semantischen Inhalten auf Basis eines medizinischen Begriffssystems. Die zugrundeliegende Annahme ist, dass die Verwendung einer einheitlichen Terminologie auf Seiten des Anfragesystems und der Wissensbasis zu qualitativ hochwertigen Ergebnissen führt. Um dies zu erreichen muss auf Seiten des Anfragesystems eine Abbildung natürlicher Sprache auf die verwendete Terminologie gewährleistet werden. Dies geschieht auf Basis einer (semi-)automatischen Verschlagwortung textbasierter Inhalte. Im Wesentlichen lassen sich folgende Fragestellungen festhalten: Automatische Verschlagwortung textbasierter Inhalte Kann eine automatische Verschlagwortung textbasierter Inhalte auf Basis eines Begriffssystems optimiert werden? Der zentrale Aspekt der vorliegenden Arbeit ist die (semi-)automatische Verschlagwortung textbasierter Inhalte auf Basis eines medizinischen Begriffssystems. Zu diesem Zweck wird der aktuelle Stand der Forschung betrachtet. Es werden eine Reihe von Tokenizern verglichen um zu erfahren welche Algorithmen sich zur Ermittlung von Wortgrenzen eignen. Speziell wird betrachtet, wie die Ermittlung von Wortgrenzen in einer domänenspezifischen Umgebung eingesetzt werden kann. Auf Basis von identifizierten Token in einem Text werden die Auswirkungen des Stemming und POS-Tagging auf die Gesamtmenge der zu analysierenden Inhalte beobachtet. Abschließend wird evaluiert wie ein kontrolliertes Vokabular die Präzision bei der Verschlagwortung erhöhen kann. Dies geschieht unter der Annahme dass domänenspezifische Inhalte auch innerhalb eines domänenspezifischen Begriffssystems definiert sind. Zu diesem Zweck wird ein allgemeines Prozessmodell entwickelt anhand dessen eine Verschlagwortung vorgenommen wird.
-
Biebricher, N.; Fuhr, N.; Lustig, G.; Schwantner, M.; Knorz, G.: ¬The automatic indexing system AIR/PHYS : from research to application (1988)
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- Date
- 16. 8.1998 12:51:22
-
Kutschekmanesch, S.; Lutes, B.; Moelle, K.; Thiel, U.; Tzeras, K.: Automated multilingual indexing : a synthesis of rule-based and thesaurus-based methods (1998)
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- Source
- Information und Märkte: 50. Deutscher Dokumentartag 1998, Kongreß der Deutschen Gesellschaft für Dokumentation e.V. (DGD), Rheinische Friedrich-Wilhelms-Universität Bonn, 22.-24. September 1998. Hrsg. von Marlies Ockenfeld u. Gerhard J. Mantwill
-
Tsareva, P.V.: Algoritmy dlya raspoznavaniya pozitivnykh i negativnykh vkhozdenii deskriptorov v tekst i protsedura avtomaticheskoi klassifikatsii tekstov (1999)
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- Date
- 1. 4.2002 10:22:41
-
Stankovic, R. et al.: Indexing of textual databases based on lexical resources : a case study for Serbian (2016)
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- Date
- 1. 2.2016 18:25:22
-
Tsujii, J.-I.: Automatic acquisition of semantic collocation from corpora (1995)
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- Date
- 31. 7.1996 9:22:19
-
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
-
Lepsky, K.; Vorhauer, J.: Lingo - ein open source System für die Automatische Indexierung deutschsprachiger Dokumente (2006)
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- Date
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Probst, M.; Mittelbach, J.: Maschinelle Indexierung in der Sacherschließung wissenschaftlicher Bibliotheken (2006)
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- Date
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