Journal ArticleDOI
Automatic personalization based on Web usage mining
TLDR
The ability to track users’ browsing behavior down to individual mouse clicks has brought the vendor and end customer closer than ever before, and it is now possible for a vendor to personalize his product message for individual customers at a massive scale, a phenomenon that is being referred to as mass customization.Abstract:
The ease and speed with which business transactions can be carried out over the Web have been a key driving force in the rapid growth of electronic commerce. Business-to-business e-commerce is the focus of much attention today, mainly due to its huge volume. While there are certainly gains to be made in this arena, most of it is the implementation of much more efficient supply management, payments, etc. On the other hand, e-commerce activity that involves the end user is undergoing a significant revolution. The ability to track users’ browsing behavior down to individual mouse clicks has brought the vendor and end customer closer than ever before. It is now possible for a vendor to personalize his product message for individual customers at a massive scale, a phenomenon that is being referred to as mass customization.read more
Citations
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Journal ArticleDOI
Item-based top-N recommendation algorithms
Mukund Deshpande,George Karypis +1 more
TL;DR: This article presents one class of model-based recommendation algorithms that first determines the similarities between the various items and then uses them to identify the set of items to be recommended, and shows that these item-based algorithms are up to two orders of magnitude faster than the traditional user-neighborhood based recommender systems and provide recommendations with comparable or better quality.
Journal ArticleDOI
Recommender system application developments
TL;DR: This paper reviews up-to-date application developments of recommender systems, clusters their applications into eight main categories, and summarizes the related recommendation techniques used in each category.
Journal ArticleDOI
Web mining for web personalization
TL;DR: This article introduces the modules that comprise a Web personalization system, emphasizing the Web usage mining module, and presents a review of the most common methods that are used as well as technical issues that occur.
Patent
Content personalization based on actions performed during a current browsing session
TL;DR: In this paper, various methods are disclosed for monitoring user browsing activities, and for using such information to provide session-specific item recommendations to users, and the recommended items may be displayed together with an option to individually deselect the recently viewed items on which the recommendations are based.
Journal ArticleDOI
Measuring Switching Costs and the Determinants of Customer Retention in Internet-Enabled Businesses: A Study of the Online Brokerage Industry
Pei-Yu Chen,Lorin M. Hitt +1 more
TL;DR: It is found that customer demographic characteristics have little effect on switching, but that systems usage measures and systems quality are associated with reduced switching, and online brokerage firms appear to have different abilities in retaining customers and have considerable control over their switching costs.
References
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Proceedings Article
Fast algorithms for mining association rules
TL;DR: Two new algorithms for solving thii problem that are fundamentally different from the known algorithms are presented and empirical evaluation shows that these algorithms outperform theknown algorithms by factors ranging from three for small problems to more than an order of magnitude for large problems.
Proceedings ArticleDOI
Mining sequential patterns
TL;DR: Three algorithms are presented to solve the problem of mining sequential patterns over databases of customer transactions, and empirically evaluating their performance using synthetic data shows that two of them have comparable performance.
Proceedings ArticleDOI
Social information filtering: algorithms for automating “word of mouth”
Upendra Shardanand,Pattie Maes +1 more
TL;DR: The implementation of a networked system called Ringo, which makes personalized recommendations for music albums and artists, and four different algorithms for making recommendations by using social information filtering were tested and compared.
Journal ArticleDOI
GroupLens: applying collaborative filtering to Usenet news
Joseph A. Konstan,Bradley N. Miller,David A. Maltz,Jonathan L. Herlocker,Lee R. Gordon,John Riedl +5 more
TL;DR: The combination of high volume and personal taste made Usenet news a promising candidate for collaborative filtering and the potential predictive utility for Usenets news was very high.