publication . Other literature type . Part of book or chapter of book . 2007

Keyword Extraction Based on PageRank

Jinghua Wang; Jianyi Liu; Cong Wang;
  • Published: 20 Jun 2007
  • Publisher: Springer Berlin Heidelberg
Abstract
Keywords are viewed as the words that represent the topic and the content of the whole text. Keyword extraction is an important technology in many areas of document processing, such as text clustering, text summarization, and text retrieval. This paper provides a keyword extraction algorithm based on WordNet and PageRank. Firstly, a text is represented as a rough undirected weighted semantic graph with WordNet, which defines synsets as vertices and relations of vertices as edges, and assigns the weight of edges with the relatedness of connected synsets. Then we apply UW-PageRank in the rough graph to do word sense disambiguation, prune the graph, and finally app...
Subjects
ACM Computing Classification System: InformationSystems_INFORMATIONSTORAGEANDRETRIEVALMathematicsofComputing_DISCRETEMATHEMATICSComputingMethodologies_DOCUMENTANDTEXTPROCESSING
free text keywords: Artificial intelligence, business.industry, business, PageRank, law.invention, law, Text graph, Natural language processing, computer.software_genre, computer, WordNet, Automatic summarization, Keyword density, Full text search, Keyword extraction, Document clustering, Information retrieval, Computer science
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Digital Humanities and Cultural Heritage
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publication . Other literature type . Part of book or chapter of book . 2007

Keyword Extraction Based on PageRank

Jinghua Wang; Jianyi Liu; Cong Wang;