Refereed full papers (journals, book chapters, international conferences)

2004

@article{KaK2004,
	vgclass =	{refpap},
	author =	{In-Ho Kang and Gil Chang Kim},
	title =	{Integration of multiple evidences based on a query type
	for web search},
	journal =	{Information Processing and Management},
	volume =	{40},
	number =	{3},
	pages =	{459--478},
	month =	{May},
	year =	{2004},
	url =	{http://dx.doi.org/10.1016/S0306-4573(03)00053-0},
	abstract =	{The massive and heterogeneous Web exacerbates IR problems
	and short user queries make them worse. The contents of web pages are
	not enough to find answer pages. PageRank compensates for the
	insufficiencies of content information. The content information and
	PageRank are combined to get better results. However, static
	combination of multiple evidences may lower the retrieval performance.
	We have to use different strategies to meet the need of a user. We can
	classify user queries as three categories according to users' intent,
	the topic relevance task, the homepage finding task, and the service
	finding task. In this paper, we present a user query classification
	method. The difference of distribution, mutual information, the usage
	rate as anchor texts and the POS information are used for the
	classification. After we classified a user query, we apply different
	algorithms and information for the better results. For the topic
	relevance task, we emphasize the content information, on the other
	hand, for the homepage finding task, we emphasize the Link information
	and the URL information. We could get the best performance when our
	proposed classification method with the OKAPI scoring algorithm was
	used.},
}