-
Newman, D.J.; Block, S.: Probabilistic topic decomposition of an eighteenth-century American newspaper (2006)
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- Date
- 22. 7.2006 17:32:00
- Source
- Journal of the American Society for Information Science and Technology. 57(2006) no.6, S.753-767
-
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
-
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
-
Lepsky, K.; Vorhauer, J.: Lingo - ein open source System für die Automatische Indexierung deutschsprachiger Dokumente (2006)
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- Date
- 24. 3.2006 12:22:02
-
Probst, M.; Mittelbach, J.: Maschinelle Indexierung in der Sacherschließung wissenschaftlicher Bibliotheken (2006)
0.01
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- Date
- 22. 3.2008 12:35:19
-
Hlava, M.M.: Automatic indexing : a matter of degree (2002)
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- Source
- Bulletin of the American Society for Information Science. 28(2002) no.1, S.12-15
-
Renz, M.: Automatische Inhaltserschließung im Zeichen von Wissensmanagement (2001)
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- Date
- 22. 3.2001 13:14:48
-
Mongin, L.; Fu, Y.Y.; Mostafa, J.: Open Archives data Service prototype and automated subject indexing using D-Lib archive content as a testbed (2003)
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- Abstract
- The Indiana University School of Library and Information Science opened a new research laboratory in January 2003; The Indiana University School of Library and Information Science Information Processing Laboratory [IU IP Lab]. The purpose of the new laboratory is to facilitate collaboration between scientists in the department in the areas of information retrieval (IR) and information visualization (IV) research. The lab has several areas of focus. These include grid and cluster computing, and a standard Java-based software platform to support plug and play research datasets, a selection of standard IR modules and standard IV algorithms. Future development includes software to enable researchers to contribute datasets, IR algorithms, and visualization algorithms into the standard environment. We decided early on to use OAI-PMH as a resource discovery tool because it is consistent with our mission.
-
Humphrey, S.M.; Névéol, A.; Browne, A.; Gobeil, J.; Ruch, P.; Darmoni, S.J.: Comparing a rule-based versus statistical system for automatic categorization of MEDLINE documents according to biomedical specialty (2009)
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- Abstract
- Automatic document categorization is an important research problem in Information Science and Natural Language Processing. Many applications, including, Word Sense Disambiguation and Information Retrieval in large collections, can benefit from such categorization. This paper focuses on automatic categorization of documents from the biomedical literature into broad discipline-based categories. Two different systems are described and contrasted: CISMeF, which uses rules based on human indexing of the documents by the Medical Subject Headings (MeSH) controlled vocabulary in order to assign metaterms (MTs), and Journal Descriptor Indexing (JDI), based on human categorization of about 4,000 journals and statistical associations between journal descriptors (JDs) and textwords in the documents. We evaluate and compare the performance of these systems against a gold standard of humanly assigned categories for 100 MEDLINE documents, using six measures selected from trec_eval. The results show that for five of the measures performance is comparable, and for one measure JDI is superior. We conclude that these results favor JDI, given the significantly greater intellectual overhead involved in human indexing and maintaining a rule base for mapping MeSH terms to MTs. We also note a JDI method that associates JDs with MeSH indexing rather than textwords, and it may be worthwhile to investigate whether this JDI method (statistical) and CISMeF (rule-based) might be combined and then evaluated showing they are complementary to one another.
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2530-2539
-
Dolamic, L.; Savoy, J.: When stopword lists make the difference (2009)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.1, S.200-203
-
Medelyan, O.; Witten, I.H.: Domain-independent automatic keyphrase indexing with small training sets (2008)
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- Source
- Journal of the American Society for Information Science and Technology. 59(2008) no.7, S.1026-1040
-
Chung, Y.M.; Lee, J.Y.: ¬A corpus-based approach to comparative evaluation of statistical term association measures (2001)
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- Source
- Journal of the American Society for Information Science and technology. 52(2001) no.4, S.283-296
-
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
-
Jones, S.; Paynter, G.W.: Automatic extractionof document keyphrases for use in digital libraries : evaluations and applications (2002)
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- Source
- Journal of the American Society for Information Science and technology. 53(2002) no.8, S.653-677
-
Dolamic, L.; Savoy, J.: Indexing and searching strategies for the Russian language (2009)
0.01
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- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2540-2547
-
Rasmussen, E.M.: Indexing and retrieval for the Web (2002)
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- Source
- Annual review of information science and technology. 37(2003), S.91-126
