The main contribution of this work is the comparison of different techniques for representing user preferences extracted by analyzing data gathered from social networks, with the aim of constructing more transparent (human-readable) and serendipitous user profiles. We compared two different user models representations: one based on keywords and one exploiting encyclopedic knowledge extracted from Wikipedia. A preliminary evaluation involving 51 Facebook and Twitter users has shown that the use of an encyclopedic-based representation better reflects user preferences, and helps to introduce new interesting topics.
Leveraging Encyclopedic Knowledge for Transparent and Serendipitous User Profiles / Narducci, Fedelucio; Musto, Cataldo; Semeraro, Giovanni; Lops, Pasquale; de Gemmis, Marco. - STAMPA. - 7899:(2013), pp. 350-352. (Intervento presentato al convegno 21st International Conference on User Modeling, Adaptation and Personalization, UMAP 2013 tenutosi a Roma, Italy nel June 10-14, 2013) [10.1007/978-3-642-38844-6_36].
Leveraging Encyclopedic Knowledge for Transparent and Serendipitous User Profiles
Fedelucio Narducci;
2013-01-01
Abstract
The main contribution of this work is the comparison of different techniques for representing user preferences extracted by analyzing data gathered from social networks, with the aim of constructing more transparent (human-readable) and serendipitous user profiles. We compared two different user models representations: one based on keywords and one exploiting encyclopedic knowledge extracted from Wikipedia. A preliminary evaluation involving 51 Facebook and Twitter users has shown that the use of an encyclopedic-based representation better reflects user preferences, and helps to introduce new interesting topics.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
