www.b-it-center.de

Context-aware Mobile Recommendation Services for Conference Participants

Download and install the application at: http://dbis.rwth-aachen.de/~kovachev/camrs/ http://goo.gl/XQWLL

Academic events: which talk to attend, who is my potential collaborator?

Dejan Kovachev, Manh Cuong Pham, Yiwei Cao — Information Systems & Databases, RWTH Aachen University, Aachen, Germany — {kovachev|pham|cao }@dbis.rwth-aachen.de

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Room 204: Paper session Hall: Poster session

Room 342: Workshop

Room 048: Round table

Auditorium: Keynote

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Collaborative filtering Web services

Android app CAMRS Mobile

Location information

Our approach: collaborative recommendation based on your research community and current location

AERCS SNA services(http://bosch.informatik.rwth-aachen.de:5080/AERCS/)

Bibliographical information (DBLP

and CiteSeerX)

SNA on co-authorship and

citation networks Smart phone

location sensing

Algorithm: collaborative filtering with contextual information 1. Identify user‘s community: similarity measure

using jaccard measure on coauthorship and citation nets. 2. Recommend top k similar researchers who are in

the same room. 3. Talk recommendation: 3.1 Rank sections where R(v,e): attendance of v at section e, K: top similar users, : ending time of section e 3.2 Recommend top n rank section

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