Visual Data Mining for Collaborative Filtering

Author:

Biba Marenglen1,Vajjhala Narasimha Rao1,Nishani Lediona1

Affiliation:

1. University of New York Tirana, Albania

Abstract

This book chapter provides a state-of-the-art survey of visual data mining techniques used for collaborative filtering. The chapter begins with a discussion on various visual data mining techniques along with an analysis of the state-of-the-art visual data mining techniques used by researchers as well as in the industry. Collaborative filtering approaches are presented along with an analysis of the state-of-the-art collaborative filtering approaches currently in use in the industry. Visual data mining can provide benefit to existing data mining techniques by providing the users with visual exploration and interpretation of data. The users can use these visual interpretations for further data mining. This chapter dealt with state-of-the-art visual data mining technologies that are currently in use apart. The chapter also includes the key section of the discussion on the latest trends in visual data mining for collaborative filtering.

Publisher

IGI Global

Reference59 articles.

1. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions

2. Aggarwal, C. C., Wolf, J. L., Wu, K. L., & Yu, P. S. (1999). Horting hatches an agg: A new graph-theoretic approach to collaborative. Proceedings of theFifth ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining, ACM Digital Library.

3. Bilsus, D., & Pazzani, M. (1998). Learning Collaborative Information Filters. Proceedings of theInt’l Conf. Machine Learning.

4. Collaborative filtering based on significances

5. Adaptation and evaluation of 3-dimensional collaborative Information visualizations.;K.Börner;Proceedings of Workshop on Empirical Evaluations of Adaptive Systems,2001

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Knowledge Discovery and Data Visualization;International Journal of Organizational and Collective Intelligence;2017-07

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3