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Query-recommendation systems based on inputted queries have become widespread. These services are effective if users cannot input relevant queries. However, the conventional systems do not take into consideration the relevance between recommended queries. This paper proposes a method of obtaining related queries and clustering them by using the history of query frequencies in query logs. We define...
Peer-to-peer approaches bring one perfect alternative for the Web content search. However, how to search and retrieve the data based on the content query is still an open problem for peer-to-peer systems. In this paper we propose History-based Multi-keywords Search(HMS) in unstructured peer-to-peer systems, which only
This paper proposes a system for finding a userpsilas interests on the Internet. It is based on his browsing behaviors and the contents of his visited pages. The system has two features. One is building userpsilas browsing interests implicitly, multiple keyword vectors, one per interest. The other is that it can
to keyword searching. Thus far, the identification of the facets was either a manual procedure, or relied on apriori knowledge of the facets that can potentially appear in the underlying collection. In this paper, we present an unsupervised technique for automatic extraction of facets useful for browsing text databases
Electronic Commerce has offered a convenient way for people to go shopping on the Internet. However, it is difficult for Internet customers to select a valuable item from the great number of various products available on line. When we use a keyword and search in a EC website, the ranking algorithm of products is
-independent approach of extracting news stories from web pages is proposed which is based on anchor text and is applicable to most websites. Experiments show our approach performs good and is better than another approach we have found. Second, a domain-based method of representing events is proposed in which hundreds of keywords
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