A New Retrieval Ranking Method based on Document Retrieval Expected Value in Chinese Document
Tao Wang, Yan Jiang, Mei Chen, Hanhu Wang
Abstract
Tao Wang, Yan Jiang, Mei Chen, Hanhu Wang
Abstract
Through the analysis of the information on the contents of the document which contained in title, abstract and keywords, find out which documents are more relativity with user's retrieval expectation, this paper adopted "Document Retrieval Expected Value" as be the indicator, builds the mathematical model for it, and then takes advantage of it to do the quantitative calculation for all documents retrieved from the document retrieval engines, such as Weipu, CNKI, etc, finally, sorts all the document retrieval expected values with the descending sorting algorithm, more accurate documents will be displayed on the front, and it will meet the user's demands for documents better.
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Through the analysis of the information on the contents of the document which contained in title, abstract and keywords, find out which documents are more relativity with user's retrieval expectation, this paper adopted "Document Retrieval Expected Value" as be the indicator, builds the mathematical model for it, and then takes advantage of it to do the quantitative calculation for all documents retrieved from the document retrieval engines, such as Weipu, CNKI, etc, finally, sorts all the document retrieval expected values with the descending sorting algorithm, more accurate documents will be displayed on the front, and it will meet the user's demands for documents better.
Key concepts: Information retrieval, Computer science, Document retrieval, Ranking (information retrieval), Sorting, Vector space model, Document clustering, Value (mathematics)