数据挖掘技术在Web推荐系统中的算法研究  

Research of data mining in Web recommendation system

作　　者：杨卓林[1] 朱明清[1] 焦运涛[1] 王冠宇[1] 

机构地区：[1]黑龙江省科学院自动化研究所,哈尔滨150090

出　　处：《黑龙江科学》2014年第7期20-22,共3页Heilongjiang Science

摘　　要：数据挖掘技术(Data Mining)是一种包含了数据库技术、人工智能技术、统计学、模式识别技术等多种计算机及数学知识的综合学科。而在数据挖掘技术的应用中,WEB数据挖掘应用已经成为当今最受追捧的数据挖掘研究方向。在包罗万象的WEB应用中,有一类对用户的喜好选项进行预测的系统被称之为推荐系统(recommendation system)。本研究主要针对现今最常见的Web应用,提出针对两种内容的推荐方式,基于对用户兴趣的预测结果和基于用户过去的购物或搜索历史。针对实现两种推荐系统所需要的具体算法进行深入研究。Data Mining is a computer and including a variety of multi-disciplinary database technology, artificial intelligence technology, statistics, pattern recognition technology and other mathematical knowledge. In the application of data mining technology, WEB data mining has become present hottest data mining research directions. In the all-encompassing WEB applications, there are a number of users preferring option prediction system called recommendation system. This article focuses on present most common Web applications, and proposes two ways of content recommendation ： 1, based on user interest prediction ; 2, based on the user＇ s shopping or past search history. It also made in-depth study of two specific algorithms needed for recommendation system.

关 键 词：数据挖掘技术 人工智能 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]