计算机工程与科学2018，Vol.40Issue(2)：231-237,7.DOI:10.3969/j.issn.1007-130X.2018.02.006
基于日志挖掘的电商查询建议方法
E-commerce query suggestion based on log mining
摘要
Abstract
Query suggestion can effectively alleviate the input burden for users,eliminate the query ambiguity,and improve theconvenience and accuracy of information retrieval.With the development of e-commerce,query suggestion is also popular in the product search of e-commerce applications.However,traditional query suggestion methods for Web search are not fully applicable in e-commerce applications.Based on the analysis of different query suggestion techniques,an e-commerce query suggestion method based on log mining is presented,which considersboth the search behaviors and shopping behaviors of users.MapReduce is used in log mining to generate the query words in an offline mode,and query suggestions are offeredto users in an online mode.Experimental results show that the presented method can improves the accuracy of querysuggestions and has good performance.关键词
查询建议/日志挖掘/电子商务/准确率/MapReduceKey words
query suggestion/log mining/E-commerce/precision/MapReduce分类
信息技术与安全科学引用本文复制引用
王菁,王若飞..基于日志挖掘的电商查询建议方法[J].计算机工程与科学,2018,40(2):231-237,7.基金项目
国家自然科学基金(61672042) （61672042）
北京市自然科学基金(4131001) （4131001）
