creators_name: Chen, Wen-Yen creators_name: Chu, Jon-Chyuan creators_name: Luan, Junyi creators_name: Bai, Hongjie creators_name: Wang, Yi creators_name: Chang, Edward Y. type: conference_item datestamp: 2009-04-06 19:10:31 lastmod: 2009-04-29 12:22:38 metadata_visibility: show title: Collaborative Filtering for Orkut Communities: Discovery of User Latent Behavior ispublished: pub full_text_status: public pres_type: paper abstract: Users of social networking services can connect with each other by forming communities for online interaction. Yet as the number of communities hosted by such websites grows over time, users have even greater need for effective commu- nity recommendations in order to meet more users. In this paper, we investigate two algorithms from very different do- mains and evaluate their effectiveness for personalized com- munity recommendation. First is association rule mining (ARM), which discovers associations between sets of com- munities that are shared across many users. Second is latent Dirichlet allocation (LDA), which models user-community co-occurrences using latent aspects. In comparing LDA with ARM, we are interested in discovering whether modeling low-rank latent structure is more effective for recommen- dations than directly mining rules from the observed data. We experiment on an Orkut data set consisting of 492, 104 users and 118, 002 communities. Our empirical comparisons using the top-k recommendations metric show that LDA performs consistently better than ARM for the community recommendation task when recommending a list of 4 or more communities. However, for recommendation lists of up to 3 communities, ARM is still a bit better. We analyze exam- ples of the latent information learned by LDA to explain this finding. To efficiently handle the large-scale data set, we parallelize LDA on distributed computers [1] and demon- strate our parallel implementation’s scalability with varying numbers of machines. date: 2009-04 pagerange: 681-681 event_title: 18th International World Wide Web Conference event_location: Madrid, Spain event_dates: April 20th-24th, 2009 event_type: conference refereed: TRUE citation: Chen, Wen-Yen and Chu, Jon-Chyuan and Luan, Junyi and Bai, Hongjie and Wang, Yi and Chang, Edward Y. (2009) Collaborative Filtering for Orkut Communities: Discovery of User Latent Behavior. In: 18th International World Wide Web Conference, April 20th-24th, 2009, Madrid, Spain. document_url: http://www2009.eprints.org/69/1/p681.pdf document_url: http://www2009.eprints.org/69/2/wychen_www09_v2.pdf