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Text-mining Based Graph Model for Keyword Extraction from Patent Documents
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Text-mining Based Graph Model for Keyword Extraction from Patent Documents
Lee, Soon Geun; Leem, Young Moon; Um, Wan Sup;
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The increasing interests on patents have led many individuals and companies to apply for many patents in various areas. Applied patents are stored in the forms of electronic documents. The search and categorization for these documents are issues of major fields in data mining. Especially, the keyword extraction by which we retrieve the representative keywords is important. Most of techniques for it is based on vector space model. But this model is simply based on frequency of terms in documents, gives them weights based on their frequency and selects the keywords according to the order of weights. However, this model has the limit that it cannot reflect the relations between keywords. This paper proposes the advanced way to extract the more representative keywords by overcoming this limit. In this way, the proposed model firstly prepares the candidate set using the vector model, then makes the graph which represents the relation in the pair of candidate keywords in the set and selects the keywords based on this relationship graph.
Relationship graph model;Patents;Keyword extraction;Text mining;
 Cited by
Coombs, J. E. & Bierly, P. E.(2006), "Measuring technological capability and performance" R&D Management, 36(4):421-438 crossref(new window)

Feldman. R., and J. Sanger(2007), "The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data" New York, NY Cambridge University Press.

G. Salton, A. Wong and C. S. Yang(1975), "A vector space model for automatic indexing" Communications of the ACM, 18:613-620 crossref(new window)

I.V. Wartburg, T. Teichert, K. Rost(2005), "Inventive progress measured by multistage patent citation analysis" Research Policy 34 (10), 1591-1607. crossref(new window)

Jae Young, Chang(2013), "A study on research trends of graph-based text representations for text mining" The Journal of The Institute of Internet, Broadcasting and Communication 13: No. 5

Jens-Erik Mai(2005), "Analysis in indexing: document and domain centered approaches" Information Processing and Management 41:599-611 crossref(new window)

Jiawei Han, Micheline Kamber(2011), "Data mining concepts and techniques" 2nd-edition Morgan Kaufmann press, 614-628

Jo, Taeho, Lee, Malrey, and Gatton, T. M.(2006), "Keyword extraction from documents using a neural network model," ICHIT'06, 2:194-197.

Kao. A. and S. R. Poteet.(2007), "Natural Language Processing and Text Mining" London Springer-Verlag, 1-7

Li, Y.R, Wang, L.H., & Hong, C. F.(2009), "Extracting the significant-rare keywords for patent analysis" Expert System with Applications, 36(6):5200-5204 crossref(new window)

Matsuo, Y., and Ishizuka, M.(2004), "Keyword extraction from a single document using word co-occurrence statistical information," International Journal on Artificial Intelligence Tools, 13:157-169. crossref(new window)

Roberston, S.(2004), "Understanding inverse document frequency: On theoretical argument for IDF" Journal of Documentation, 60(5):503-520. crossref(new window)

Yu, J. X., Kitsuregawa, M., and Leong, H. V.(2006), "Keyword Extraction using Support Vector Machine," Lecture notes in computer science, 4016:85-96.

Wang, J., Liu, J., Wang, and Cong(2007), "Keyword extraction based on PageRank," Lecture notes in computer science, 857-864.