Abstract
As the Web has become an important channel of information floods, users have had difficulty on identifying what they really want from huge amounts of rubbish-like information provided by the Web search engines when utilizing the Web’s low-cost information. This is because most users can only give inadequate (or incomplete) expressions for representing their requirements when querying the Web. In this paper, a heuristic model is proposed for tackling the inadequate query problem. Our approach is based on the potentially useful relationships among terms, called term association rules, in text corpus. For identifying quality information, a constraint is designed for capturing the goodness of queries. The heuristic information in our model assists users in expressing their queries desired.
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Qin, Z., Liu, L., Zhang, S. (2004). Mining Term Association Rules for Heuristic Query Construction. In: Dai, H., Srikant, R., Zhang, C. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2004. Lecture Notes in Computer Science(), vol 3056. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24775-3_18
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DOI: https://doi.org/10.1007/978-3-540-24775-3_18
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