-
Liu, G.Z.: Semantic vector space model : implementation and evaluation (1997)
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- Source
- Journal of the American Society for Information Science. 48(1997) no.5, S.395-417
-
Goller, C.; Löning, J.; Will, T.; Wolff, W.: Automatic document classification : a thourough evaluation of various methods (2000)
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- Abstract
- (Automatic) document classification is generally defined as content-based assignment of one or more predefined categories to documents. Usually, machine learning, statistical pattern recognition, or neural network approaches are used to construct classifiers automatically. In this paper we thoroughly evaluate a wide variety of these methods on a document classification task for German text. We evaluate different feature construction and selection methods and various classifiers. Our main results are: (1) feature selection is necessary not only to reduce learning and classification time, but also to avoid overfitting (even for Support Vector Machines); (2) surprisingly, our morphological analysis does not improve classification quality compared to a letter 5-gram approach; (3) Support Vector Machines are significantly better than all other classification methods
-
Buckley, C.; Allan, J.; Salton, G.: Automatic routing and retrieval using Smart : TREC-2 (1995)
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- Abstract
- The Smart information retrieval project emphazises completely automatic approaches to the understanding and retrieval of large quantities of text. The work in the TREC-2 environment continues, performing both routing and ad hoc experiments. The ad hoc work extends investigations into combining global similarities, giving an overall indication of how a document matches a query, with local similarities identifying a smaller part of the document that matches the query. The performance of ad hoc runs is good, but it is clear that full advantage of the available local information is not been taken advantage of. The routing experiments use conventional relevance feedback approaches to routing, but with a much greater degree of query expansion than was previously done. The length of a query vector is increased by a factor of 5 to 10 by adding terms found in previously seen relevant documents. This approach improves effectiveness by 30-40% over the original query
-
Bloomfield, M.: Indexing : neglected and poorly understood (2001)
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- Date
- 5. 6.2001 12:25:05
-
Fauzi, F.; Belkhatir, M.: Multifaceted conceptual image indexing on the world wide web (2013)
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- Date
- 5. 9.2014 10:18:18
-
Snajder, J.; Dalbelo Basic, B.D.; Tadic, M.: Automatic acquisition of inflectional lexica for morphological normalisation (2008)
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- Source
- Information processing and management. 44(2008) no.5, S.1720-1731
-
Greiner-Petter, A.; Schubotz, M.; Cohl, H.S.; Gipp, B.: Semantic preserving bijective mappings for expressions involving special functions between computer algebra systems and document preparation systems (2019)
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- Date
- 20. 1.2015 18:30:22
-
Golub, K.; Lykke, M.; Tudhope, D.: Enhancing social tagging with automated keywords from the Dewey Decimal Classification (2014)
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- Source
- Journal of documentation. 70(2014) no.5, S.801-828
-
Vlachidis, A.; Tudhope, D.: ¬A knowledge-based approach to information extraction for semantic interoperability in the archaeology domain (2016)
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- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.5, S.1138-1152
-
Husevag, A.-S.R.: Named entities in indexing : a case study of TV subtitles and metadata records (2016)
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- Source
- Proceedings of the 15th European Networked Knowledge Organization Systems Workshop (NKOS 2016) co-located with the 20th International Conference on Theory and Practice of Digital Libraries 2016 (TPDL 2016), Hannover, Germany, September 9, 2016. Edi. by Philipp Mayr et al. [http://ceur-ws.org/Vol-1676/=urn:nbn:de:0074-1676-5]
-
Strobel, S.; Marín-Arraiza, P.: Metadata for scientific audiovisual media : current practices and perspectives of the TIB / AV-portal (2015)
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- Date
- 5. 6.2017 11:19:32
-
Li, X.; Zhang, A.; Li, C.; Ouyang, J.; Cai, Y.: Exploring coherent topics by topic modeling with term weighting (2018)
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- Date
- 5. 9.2014 10:18:18
-
Zhang, Y.; Zhang, C.; Li, J.: Joint modeling of characters, words, and conversation contexts for microblog keyphrase extraction (2020)
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- Source
- Journal of the Association for Information Science and Technology. 71(2020) no.5, S.553-567
-
Kajanan, S.; Bao, Y.; Datta, A.; VanderMeer, D.; Dutta, K.: Efficient automatic search query formulation using phrase-level analysis (2014)
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- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.5, S.1058-1075
-
Tavakolizadeh-Ravari, M.: Analysis of the long term dynamics in thesaurus developments and its consequences (2017)
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- Abstract
- Die Arbeit analysiert die dynamische Entwicklung und den Gebrauch von Thesaurusbegriffen. Zusätzlich konzentriert sie sich auf die Faktoren, die die Zahl von Indexbegriffen pro Dokument oder Zeitschrift beeinflussen. Als Untersuchungsobjekt dienten der MeSH und die entsprechende Datenbank "MEDLINE". Die wichtigsten Konsequenzen sind: 1. Der MeSH-Thesaurus hat sich durch drei unterschiedliche Phasen jeweils logarithmisch entwickelt. Solch einen Thesaurus sollte folgenden Gleichung folgen: "T = 3.076,6 Ln (d) - 22.695 + 0,0039d" (T = Begriffe, Ln = natürlicher Logarithmus und d = Dokumente). Um solch einen Thesaurus zu konstruieren, muss man demnach etwa 1.600 Dokumente von unterschiedlichen Themen des Bereiches des Thesaurus haben. Die dynamische Entwicklung von Thesauri wie MeSH erfordert die Einführung eines neuen Begriffs pro Indexierung von 256 neuen Dokumenten. 2. Die Verteilung der Thesaurusbegriffe erbrachte drei Kategorien: starke, normale und selten verwendete Headings. Die letzte Gruppe ist in einer Testphase, während in der ersten und zweiten Kategorie die neu hinzukommenden Deskriptoren zu einem Thesauruswachstum führen. 3. Es gibt ein logarithmisches Verhältnis zwischen der Zahl von Index-Begriffen pro Aufsatz und dessen Seitenzahl für die Artikeln zwischen einer und einundzwanzig Seiten. 4. Zeitschriftenaufsätze, die in MEDLINE mit Abstracts erscheinen erhalten fast zwei Deskriptoren mehr. 5. Die Findablity der nicht-englisch sprachigen Dokumente in MEDLINE ist geringer als die englische Dokumente. 6. Aufsätze der Zeitschriften mit einem Impact Factor 0 bis fünfzehn erhalten nicht mehr Indexbegriffe als die der anderen von MEDINE erfassten Zeitschriften. 7. In einem Indexierungssystem haben unterschiedliche Zeitschriften mehr oder weniger Gewicht in ihrem Findability. Die Verteilung der Indexbegriffe pro Seite hat gezeigt, dass es bei MEDLINE drei Kategorien der Publikationen gibt. Außerdem gibt es wenige stark bevorzugten Zeitschriften."
-
Needham, R.M.; Sparck Jones, K.: Keywords and clumps (1985)
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- Footnote
- Original in: Journal of documentation 20(1964) no.1, S.5-15.
