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In cross-language information retrieval (CLIR), the query sentence is often combined with a series of query keywords, rather than a complete natural sentence. Lack of necessary contextual syntactic information in such a query sentence makes it impossible to achieve a unique translation of the query sentence with
features of objects in sample images. A user places a keyword-based query first and then retrieves desired images by visual content-based query. A prototype MIQR system was implemented and is available at http://140.113.216.66/WebImageSearch for online demo, and public evaluation. We also conducted experiments over a
Applying automatic summarization to search engine can make it easier for users to find out the content of the Web page. In this paper, the results of search engine are analyzed. On the basis of query keywords expansion, we propose a new summary approach which calculates the sentence weight utilizing the information of
This paper proposes an approach based on query expansion and node aggregation under the unstructured peer-to-peer network. This approach can find the relationships of keywords and nodes automatically, then record the information on each local node and update it continuously. In the future retrieval, the purpose of
A method of multi-text fusion computation is discussed in this paper which extracts the common features automatically by using text fusion. When search the information in a special domain, the keywords are picked out by using relative sample muster fusion, keywords' flexible control is realized by regulating the
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