Serendipitous Encounters along Dynamically Personalized Museum Tours.
Leo Iaquinta, Marco de Gemmis, Pasquale Lops, Giovanni Maria Semeraro, Piero Molino · IIR eBooks · 2010
Today Recommender Systems (RSs) are commonly used with various purposes, especially dealing with e-commerce and information filtering tools. Content-based RSs rely on the concept of similarity between items. It is a common belief that the user is interested in what is similar to what she has already bought/searched/visited. We believe that there are some contexts in which this assumption is wrong: it is the case of acquiring unsearched but still useful items or pieces of information. This is called serendipity. Our purpose is to stimulate users and facilitate these serendipitous encounters to happen. The paper presents a hybrid recommender system that joins a content-based approach and serendipitous heuristics in order to provide also surprising suggestions. The reference scenario concerns with personalized tours in a museum and serendipitous items are introduced by slight diversions on the context-aware tours. 1. BACKGROUND AND MOTIVATION RSs allow a customized information access for targeted domains. They provide the users with personalized advices based on their needs, preferences and usage patterns. Sometimes RSs can only recommend items that score highly against the user’s profile and, consequently, the user is limited to obtain advices only about items too similar to those she already knows. This drawback is referred as over-specialization and it prevents surprising finding from taking place. Indeed, the RSs are required to provide novel and even serendipitous ∗The full version will appear in A. Lazinica (editor), E-Commerce, ISBN 978-953-7619-X-X, electronic version freely available at http://intechweb.org. Appears in the Proceedings of the 1st Italian Information Retrieval Workshop (IIR’10), January 27–28, 2010, Padova, Italy. http://ims.dei.unipd.it/websites/iir10/index.html Copyright owned by the authors. advices. As explained by Herlocker [2], novelty occurs when the system suggests an unknown item that the user might have autonomously discovered. A serendipitous recommendation helps the user to find a surprisingly interesting item that she might not have otherwise discovered (or it would have been really hard to discover). The idea of serendipity has a link with de Bono’s “lateral thinking” [1] which consists not to think in a selective and sequential way, but accepting accidental aspects, that seem not to have relevance or simply are not sought for. This kind of behavior helps the awareness of serendipitous events, especially when the user is allowed to explore alternatives to satisfy her curiosity. Therefore the demonstrative scenario concerns personalized tours within a museum. Indeed, in addition to the “classical” recommendations that exploit the learned user profile, the system provides also programmatically supposed serendipitous recommendations and it arranges the whole of them in a personalized tour. The serendipitous suggested items are selected exploiting the learned user profile so that they cause slight diversions on the personalized tour. Indeed the content-base recommender module allows to infer the most interesting items for the active user and a personalized tour is proposed according to the spatial layout, the user behavior and the time constraint. But the resulting tour potentially suffers from overspecialization and, consequently, some items can be found no so interesting for the user. Therefore the user starts to divert from suggested path considering other items along the path with growing attention. On the other hand, also when the recommended items are actually interesting for the user, she does not move with blinkers, i.e. she does not stop from seeing artworks along the suggested path. These are opportunities for serendipitous encounters. These considerations suggest to perturb the optimal path with items that are programmatically supposed to be serendipitous for the active user. Perturbing the optimal path with slight diversions does not compromise the system benefit to guide the user across the museum under a time constraint because the user behavior is constantly monitored and personalized tour *