A negative category based approach for Wikipedia document classification

Murugeshan, Meenakshi Sundaram; Lakshmi, K.; Mukherjee, Saswati

doi:10.1504/ijkedm.2010.032582

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…For instance, Murugeshan et al (2010) presented a profile based method for Wikipedia XML document classification, using negative category information. Farhoodi et al (2009) presented an automatic web page classification method, which they tested in Persian Wikipedia.…”

Section: Text Classificationmentioning

confidence: 99%

The People’s Encyclopedia Under the Gaze of the Sages: A Systematic Review of Scholarly Research on Wikipedia

et al. 2012

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Wikipedia has become one of the ten most visited sites on the Web, and the world's leading source of Web reference information. Its rapid success has inspired hundreds of scholars from various disciplines to study its content, communication and community dynamics from various perspectives. This article presents a systematic review of scholarly research on Wikipedia. We describe our detailed, rigorous methodology for identifying over 450 scholarly studies of Wikipedia. We present the WikiLit website (http://wikilit.referata.com), where most of the papers reviewed here are described in detail. In the major section of this article, we then categorize and summarize the studies. An appendix features an extensive list of resources useful for Wikipedia researchers.

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Section: Text Classificationmentioning

confidence: 99%

The People’s Encyclopedia Under the Gaze of the Sages: A Systematic Review of Scholarly Research on Wikipedia

et al. 2012

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“…They demonstrated the pertinence of content-based and context-based features extracted from web pages in the proposed classification method. Murugeshan et al [89] presented a profile based method for Wikipedia XML document classification, using negative category information. Ray et al [111] discussed automatic question classification, a module of a question answering system.…”

Section: Information Retrievalmentioning

confidence: 99%

Excavating the mother lode of human-generated text: A systematic review of research that uses the wikipedia corpus

Mehdi

Okoli

Mesgari

et al. 2017

Information Processing & Management

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Although primarily an encyclopedia, Wikipedia's expansive content provides a knowledge base that has been continuously exploited by researchers in a wide variety of domains. This article systematically reviews the scholarly studies that have used Wikipedia as a data source, and investigates the means by which Wikipedia has been employed in three main computer science research areas: information retrieval, natural language processing, and ontology building. We report and discuss the research trends of the identified and examined studies. We further identify and classify a list of tools that can be used to extract data from Wikipedia, and compile a list of currently available data sets extracted from Wikipedia.

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