Development Trends and Prospects of Research on Quality Evaluation Techniques for Text Information Retrieval
More than 997 million Chinese netizens search for information by inputting text into search engines,94.1％of users reported that the search engine returned results containing information that was not expected by the user,and 28.5％of users expressed distrust of the search results provided by the search engine.This article first analyzes the current research status of text information retrieval quality evaluation technology at home and abroad,the existing research on the evaluation of text information retrieval results is mainly based on the assumption that the query term is the mapping of user search needs,using diversified search results technology to meet the information search needs of different users as much as possible.Then,the personalized retrieval intention of users greatly affects the credibility judgment of retrieval results,main challenges faced by the development of text information retrieval quality evaluation tech-nology are presented from three dimensions:improving the accuracy of information retrieval quality evaluation,enhancing user retrieval experience,and strengthening user privacy protection.Based on these,three main technological research trends and research ideas are proposed,including the construction of a dynamic evaluation model for user experience enhancement in information retrieval,informa-tion quality evaluation methods based on convolutional neural networks,and retrieval intent recognition methods for user privacy protection.
NETL
NSTL
万方数据
