-
Short, M.: Text mining and subject analysis for fiction; or, using machine learning and information extraction to assign subject headings to dime novels (2019)
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- Abstract
- This article describes multiple experiments in text mining at Northern Illinois University that were undertaken to improve the efficiency and accuracy of cataloging. It focuses narrowly on subject analysis of dime novels, a format of inexpensive fiction that was popular in the United States between 1860 and 1915. NIU holds more than 55,000 dime novels in its collections, which it is in the process of comprehensively digitizing. Classification, keyword extraction, named-entity recognition, clustering, and topic modeling are discussed as means of assigning subject headings to improve their discoverability by researchers and to increase the productivity of digitization workflows.
- Theme
- Data Mining
-
Bi, Y.: Sentiment classification in social media data by combining triplet belief functions (2022)
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- Abstract
- Sentiment analysis is an emerging technique that caters for semantic orientation and opinion mining. It is increasingly used to analyze online reviews and posts for identifying people's opinions and attitudes to products and events in order to improve business performance of companies and aid to make better organizing strategies of events. This paper presents an innovative approach to combining the outputs of sentiment classifiers under the framework of belief functions. It consists of the formulation of sentiment classifier outputs in the triplet evidence structure and the development of general formulas for combining triplet functions derived from sentiment classification results via three evidential combination rules along with comparative analyses. The empirical studies have been conducted on examining the effectiveness of our method for sentiment classification individually and in combination, and the results demonstrate that the best combined classifiers by our method outperforms the best individual classifiers over five review datasets.
-
Pejtersen, A.M.: Design of a classification scheme for fiction based on an analysis of actual user-librarian communication, and use of the scheme for control of librarians' search strategies (1980)
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- Date
- 5. 8.2006 13:22:44
-
Beghtol, C.: Toward a theory of fiction analysis for information storage and retrieval (1992)
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- Date
- 5. 8.2006 13:22:08
-
Hauff-Hartig, S.: Automatische Transkription von Videos : Fernsehen 3.0: Automatisierte Sentimentanalyse und Zusammenstellung von Kurzvideos mit hohem Aufregungslevel KI-generierte Metadaten: Von der Technologiebeobachtung bis zum produktiven Einsatz (2021)
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- Date
- 22. 5.2021 12:43:05
-
Raieli, R.: ¬The semantic hole : enthusiasm and caution around multimedia information retrieval (2012)
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- Date
- 22. 1.2012 13:02:10
- Source
- Knowledge organization. 39(2012) no.1, S.13-22
-
Weimer, K.H.: ¬The nexus of subject analysis and bibliographic description : the case of multipart videos (1996)
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- Source
- Cataloging and classification quarterly. 22(1996) no.2, S.5-18
-
Chen, S.-J.; Lee, H.-L.: Art images and mental associations : a preliminary exploration (2014)
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- 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
-
White, M.D.; Marsh, E.E.: Content analysis : a flexible methodology (2006)
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- Source
- Library trends. 55(2006) no.1, S.22-45
-
Sauperl, A.: Subject determination during the cataloging process : the development of a system based on theoretical principles (2002)
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- Date
- 27. 9.2005 14:22:19
-
Bade, D.: ¬The creation and persistence of misinformation in shared library catalogs : language and subject knowledge in a technological era (2002)
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- Date
- 22. 9.1997 19:16:05
