Leveraging encyclopedic knowledge for transparent and serendipitous user profiles
|Leveraging encyclopedic knowledge for transparent and serendipitous user profiles|
|Author(s)||Narducci F., Musto C., Semeraro G., Lops P., De Gemmis M.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||Unknown (Extra: Encyclopedic knowledge, Facebook, Human-readable, User models, User profile, Wikipedia, Mathematical models, Social networking (online), Knowledge management)|
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Leveraging encyclopedic knowledge for transparent and serendipitous user profiles is a 2013 conference paper written in English by Narducci F., Musto C., Semeraro G., Lops P., De Gemmis M. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
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.
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