Mining Wikipedia's snippets graph: First step to build a new knowledge base
|Mining Wikipedia's snippets graph: First step to build a new knowledge base|
|Author(s)||Wira-Alam A., Mathiak B.|
|Published in||CEUR Workshop Proceedings|
|Keyword(s)||Knowledge base, Knowledge extraction, Wikipedia (Extra: Extracting information, Knowledge base, Knowledge extraction, Question Answering, Text snippets, Textual contexts, Wikipedia, Wikipedia articles, Hypertext systems, Knowledge based systems, Web services, Websites, Data mining)|
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In this paper, we discuss the aspects of mining links and text snippets from Wikipedia as a new knowledge base. Current knowledge base, e.g. DBPedia, covers mainly the structured part of Wikipedia, but not the content as a whole. Acting as a complement, we focus on extracting information from the text of the articles. We extract a database of the hyperlinks between Wikipedia articles and populate them with the textual context surrounding each hyperlink. This would be useful for network analysis, e.g. to measure the influence of one topic on another, or for question-answering directly (for stating the relationship between two entities). First, we describe the technical parts related to extracting the data from Wikipedia. Second, we specify how to represent the data extracted as an extended triple through a Web service. Finally, we discuss the usage possibilities upon our expectation and also the challenges.
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