Context-aware Mobile Recommendation Services for Conference Participants

1,309 views

Published on

Published in: Business, Technology
1 Comment
2 Likes
Statistics
Notes
No Downloads
Views
Total views
1,309
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
10
Comments
1
Likes
2
Embeds 0
No embeds

No notes for slide

Context-aware Mobile Recommendation Services for Conference Participants

  1. 1. www.b-it-center.de Dejan Kovachev, Manh Cuong Pham, Yiwei Cao — Information Systems & Databases, RWTH Aachen University, Aachen, Germany — {kovachev|pham|cao }@dbis.rwth-aachen.de Context-aware Mobile Recommendation Services for Conference ParticipantsAcademic events: which talk to attend, who is my potential collaborator? ? ? ? ? ? Auditorium: Keynote Room 342: Workshop Room 204: Paper session Hall: Poster session Room 048: Round tableOur approach: collaborative recommendation based on your research community and current location AERCS SNA services(http://bosch.informatik.rwth- Location Algorithm: collaborative filtering with contextual aachen.de:5080/AERCS/) information information 1. Identify user‘s community: similarity measure sim(u , v) =α ∗ scoreauthor (u, v) + (1 − α ) ∗ scorecitation (u, v) using jaccard measure on coauthorship and citation nets. 2. Recommend top k similar researchers who are in Bibliographical SNA on co- the same room.information (DBLP authorship and Smart phone 3. Talk recommendation: and CiteSeerX) citation networks location sensing 3.1 Rank sections rank (e, u , t ) =β t ∗ ∑ sim(u , v) R(v, e) v∈K where 1, t < eend βt =  Collaborative filtering 0, otherwise R(v,e): attendance of v at section e, K: top similar users, Web services eend : ending time of section e 3.2 Recommend top n rank section Download and install the application at: http://dbis.rwth-aachen.de/~kovachev/camrs/ http://goo.gl/XQWLL Android app CAMRS Mobile

×