Recommending multimedia visiting paths in cultural heritage applications

Abstract

The valorization and promotion of worldwide Cultural Heritage by the adoption of Information and Communication Technologies represent nowadays some of the most important research issues with a large variety of potential applications. This challenge is particularly perceived in the Italian scenario, where the artistic patrimony is one of the most diverse and rich of the world, able to attract millions of visitors every year to monuments, archaeological sites and museums. In this paper, we present a general recommendation framework able to uniformly manage heterogeneous multimedia data coming from several web repositories and to provide context-aware recommendation techniques supporting intelligent multimedia services for the users-i.e. dynamic visiting paths for a given environment. Specific applications of our system within the cultural heritage domain are proposed by means of real case studies in the mobile environment related both to an outdoor and indoor scenario, together with some results on user's satisfaction and system accuracy

Recommender Systems and Social Networks: an application in Cultural Heritage

“…As in our previous work [4,5,7,8], we evaluate the impact of the proposed system on users engaged in several search tasks of multimedia items and compared its performances with the well-known Panoramio system 2 that, in turn, provides basic search mechanisms.…”

“…To this purpose, we employ high-order star-structured coclustering techniques -that some of the authors have adopted in previous work [14,7,8] -to address the problem of heterogeneous data pre-filtering.…”

“…On the other hand, the Recommender Engine exploits proper JAVA libraries (some developed for the system presented in [5] and integrated with coclustering libraries [7] and the rank refining procedure 1 ) to accomplish its tasks. Finally, a user can interact with our system using at the moment an Android Multimedia Guide App exploiting Google Map API.…”

SOS: A multimedia recommender System for Online Social networks

“…Eventually, a recommendation strategy should be able to provide users with relevant information depending on the context [20,9,21] (i.e. user location, observed items, etc.)…”

“…Generally, they help people in retrieving information that match their preferences by recommending products or services from a large number of candidates [1], and have been proposed over the last years to support people in making decisions in various contexts: what items to buy [2], which photo or movie to watch [3,4], which music to listen [5], what travels to do [6], who they can invite to their social network [7], which artwork could be interesting within an art collection or even to suggest visiting paths in Cultural Heritage applications [8,9,10,11,12], just to make some examples.…”