RecoDiver: Browsing behavior-based recommendations on dynamic graphs

Issue title: Recommender Systems

Article type: Research Article

Authors: Neumann, Andreas W. | Philipp, Marc | Riedel, Felix

Affiliations: Institute of Information Systems and Management, Universität Karlsruhe (TH), 76128 Karlsruhe, Germany. E-mails: {a.neumann, philipp, riedel}@iism.uni-karlsruhe.de

Abstract: Various kinds of recommendation services open to the general public have recently been integrated into the website of the University Library of Karlsruhe as a test bed for information providers and e-commerce alike. This contribution reports on the development of RecoDiver, a graph-based user interface for behavior-based recommender systems. A Java applet integrated into the library's online catalog dynamically displays recommended further documents in a clickable graph centered around the document of interest to the user. A local view of the complete graph of recommendations is presented in a radial tree layout based on a minimum spanning tree with animated graph transitions featuring interpolations by polar coordinates to avoid crisscrossings. Further graph search tools like a selectable histogram of years of publication are available as well. This article portrays the user interface as well as the distributed web service architecture behind it and features an evaluation by user surveys showing the preference of users compared to the common lists of recommended items.

Keywords: Recommender system, user interface, consumer buying behavior, real-world application

DOI: 10.3233/AIC-2008-0434

Journal: AI Communications, vol. 21, no. 2-3, pp. 177-183, 2008