网购平台搜索功能的质量评估方法研究

发布时间：2018-04-13 19:36

本文选题：搜索引擎 + 质量因素　；参考：《计算机科学》2017年11期

【摘要】：随着大数据的迅速发展,大数据应用层出不穷,诸如网购零售平台、人脸识别系统、智能决策系统、自助客服、看病导医系统等典型的大数据应用使得人们的生活越发便捷。搜索系统是人们最常使用的大数据应用之一。然而,搜索系统在不同平台上的功能各有侧重,其标准尚且不完善,搜索的质量参次不齐,无法得到保障。与普通的文本搜索引擎相比,网购平台的搜索引擎增加了分类检索、筛选等特色功能,其质量的评价与保障更为复杂。通过对网络零售平台的搜索功能进行研究,针对网购平台搜索功能的质量评价提出了质量参考因素,针对质量因素提出了若干评价指标以及相应的实现算法,并通过实验来论证了质量指标的有效性。
[Abstract]:With the rapid development of big data, big data has been used one after another, such as online retail platform, face recognition system, intelligent decision system, self-service, medical guidance system and so on, which make people's life more convenient.Search system is one of the most commonly used big data applications.However, the function of search system on different platforms has its own emphasis, its standard is not perfect, and the quality of search is not uniform, so it can not be guaranteed.Compared with the common text search engine, the search engine of the online shopping platform has added the characteristic functions such as classified search, screening and so on, and the evaluation and guarantee of its quality is more complicated.Through the research on the search function of the online retail platform, this paper puts forward the quality reference factors for the quality evaluation of the search function of the online shopping platform, and puts forward some evaluation indexes and corresponding realization algorithms for the quality factors.The validity of the quality index is proved by experiments.
【作者单位】：南京理工大学计算机科学与工程学院;南通大学计算机科学与技术学院;
【基金】：国家自然科学基金(61402229,61502233) 江苏省博士后基金(1401043B) 南京大学软件新技术国家重点实验室开放式基金(KFKT2015B10) 江苏省高校自然科学研究项目(15KJB520030)资助
【分类号】：TP391.3

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