DocumentCode
2875729
Title
Semantic User Interaction Profiles for Better People Recommendation
Author
Stan, Johann ; Do, Viet-Hung ; Maret, Pierre
Author_Institution
Centre de Villarceaux, Alcatel-Lucent Bell Labs. France, France
fYear
2011
fDate
25-27 July 2011
Firstpage
434
Lastpage
437
Abstract
In this paper we present a methodology for learning user profiles from content shared by people on Social Platforms. Such profiles are specifically tailored to reflect the user´s degree of interactivity related to the topics they are writing about. The main novelty in our work is the introduction of Linked Data in the content extraction process and the definition of specific scores to measure expertise and interactivity.
Keywords
content management; data analysis; social networking (online); user interfaces; content extraction process; linked data introduction; people recommendation; semantic user interaction; social platform; user degree; user profile learning; Data mining; Entropy; Knowledge based systems; Semantics; Twitter; Vocabulary; analysis; linked data; recommendation; semantic; social network; user profile;
fLanguage
English
Publisher
ieee
Conference_Titel
Advances in Social Networks Analysis and Mining (ASONAM), 2011 International Conference on
Conference_Location
Kaohsiung
Print_ISBN
978-1-61284-758-0
Electronic_ISBN
978-0-7695-4375-8
Type
conf
DOI
10.1109/ASONAM.2011.21
Filename
5992638
Link To Document