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query-keywords are used as a basis for sentence extraction. Results obtained from experiments performed have shown that such a combined approach can provide very interesting similarity calculation and re-ranking measure. This can be used with reasonable efficiency to detect duplications on search results generated by
relational database of web pages. So there are many researches focusing on the search in these relational database with keywords, compared with these researches, our algorithms are mainly based on bags using the greedy algorithms and supporting the phrase recognition by utilizing multiple dictionaries. We make a comparison
The World Wide Web is growing at a rate of about a million pages per day, making it tougher for search engines to extract relevant information for its users. Earlier Search Engines used simple indexing techniques to search for keywords in websites and gave more weightage to pages with higher frequency of keyword
-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
is considered as more interesting and useful. Most of recent search engines are designed based on only measuring the similarity between keywords and articles. However, the social relations between authors of articles and searcher have not been taken into account in recent research. Therefore, in order to improve the
recognition of the query and the analysis of structure of Web pages. Mutual information (MI) between keywords is used to recognize query phrases; Useful information for the summary is mined from the structure of Web pages. Experimental results show that the improved algorithm performs better in the speed and accuracy of
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