Web personalization and recommender systems

Shlomo Berkovsky, Jill Freyne

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

30 Citations (Scopus)


The quantity of accessible information has been growing rapidly and far exceeded human processing capabilities. The sheer abundance of information often prevents users from discovering the desired information, or aggravates making informed and correct choices. This highlights the pressing need for intelligent personalized applications that simplify information access and discovery by taking into account users' preferences and needs. One type of personalized application that has recently become tremendously popular in research and industry is recommender systems. These provide to users personalized recommendations about information and products they may be interested to examine or purchase. Extensive research into recommender systems has yielded a variety of techniques, which have been published at a variety of conferences and adopted by numerous Web-sites. This tutorial will provide the participants with broad overview and thorough understanding of algorithms and practically deployed Web and mobile applications of personalized technologies.
Original languageEnglish
Title of host publicationProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
PublisherAssociation for Computing Machinery (ACM)
Number of pages2
ISBN (Electronic)9781450336642
Publication statusPublished - 2015
Externally publishedYes
Event21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2015 - Sydney, Australia
Duration: 10 Aug 201513 Aug 2015


Other21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2015


  • Human-computer interaction
  • interactive search
  • generalized binary search
  • recommender systems
  • active learning


Dive into the research topics of 'Web personalization and recommender systems'. Together they form a unique fingerprint.

Cite this