Abstract
In the paper, we proposed a general framework that could automatically extract key-phrases from a collection of web pages concerning a specific topic with the help of The Free Dictionary and then construct a personal knowledge base. Both the base and visual feature in a web page are used to calculate the weight of each candidate phrase. The system extracts top p% key-phrases for each web page based on these two features and then generates a term set using union operators. Next, the system builds the relationships between terms in the term set by referencing The Free Dictionary, and then generates a list of terms sorted by weights. With the top q terms specified by users, a semantic graph can be constructed to present the part of a personal knowledge base, which shows the relationships between terms from the same domain. Finally, the experimental results show that the key-phrases generated by the proposed extractor are with good quality and acceptable for humans.
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Huang, YF., Ciou, CS. (2012). Constructing Personal Knowledge Base: Automatic Key-Phrase Extraction from Multiple-Domain Web Pages. In: Cao, L., Huang, J.Z., Bailey, J., Koh, Y.S., Luo, J. (eds) New Frontiers in Applied Data Mining. PAKDD 2011. Lecture Notes in Computer Science(), vol 7104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28320-8_6
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DOI: https://doi.org/10.1007/978-3-642-28320-8_6
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