kNN processing with co-space distance in SoLoMo systems

With the increasing popularity of smart phones, SoLoMo (Social-Location-Mobile) systems are expected to be fast-growing and become a popular mobile social networking platform. A main challenge in such systems is on the creation of stable links between users. For each online user, the current SoLoMo system continuously returns his/her kNN (k Nearest Neighbor) users based on their geo-locations. Such a recommendation approach is simple, but fails to create sustainable friendships. Instead, it would be more effective to tap onto the existing social relationships in conventional social networks, such as Facebook and Twitter, to provide a ''better'' friend recommendations. To measure the similarity between users, we propose a new metric, co-space distance, by considering both the user distances in the real world (physical distance) and the virtual world (social distance). The co-space distance measures the similarity of two users in the SoLoMo system. We compute the social distances between users based on their public information in the conventional social networks, which can be achieved by a few MapReduce jobs. To facilitate efficient computation of the social distance, we build a distributed index on top of the key-value store, and maintain the users' geo-locations using an R-tree. For each query on finding potential friends around a location, we return kNN neighbors to each user based on their co-space distances. We propose a progressive top-k processing strategy and an adaptive-caching strategy to facilitate efficient query processing. Experiments with Gowalla dataset show the effectiveness and efficiency of our recommendation approach.

[1]  Lotfi Ben Romdhane,et al.  A robust ant colony optimization-based algorithm for community mining in large scale oriented social graphs , 2013, Expert Syst. Appl..

[2]  Seung-won Hwang,et al.  Minimal probing: supporting expensive predicates for top-k queries , 2002, SIGMOD '02.

[3]  Kun-Qing Xie,et al.  An experimental study of large-scale mobile social network , 2009, WWW '09.

[4]  Lyle H. Ungar,et al.  Statistical Relational Learning for Link Prediction , 2003 .

[5]  Patrick Valduriez,et al.  Processing Top-k Queries in Distributed Hash Tables , 2007, Euro-Par.

[6]  Beng Chin Ooi,et al.  Indexing the Distance: An Efficient Method to KNN Processing , 2001, VLDB.

[7]  Hanan Samet,et al.  Distance browsing in spatial databases , 1999, TODS.

[8]  Hong Joo Lee,et al.  Use of social network information to enhance collaborative filtering performance , 2010, Expert Syst. Appl..

[9]  Wei Zeng,et al.  A unified framework for recommending items, groups and friends in social media environment via mutual resource fusion , 2013, Expert Syst. Appl..

[10]  Kian-Lee Tan,et al.  G-tree: an efficient index for KNN search on road networks , 2013, CIKM.

[11]  Yoon Ho Cho,et al.  A user-oriented contents recommendation system in peer-to-peer architecture , 2004, Expert Syst. Appl..

[12]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[13]  Wei-Ying Ma,et al.  Recommending friends and locations based on individual location history , 2011, ACM Trans. Web.

[14]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[15]  Xing Xie,et al.  GeoLife2.0: A Location-Based Social Networking Service , 2009, 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware.

[16]  Gerhard Weikum,et al.  IO-Top-k: index-access optimized top-k query processing , 2006, VLDB.

[17]  Mao Ye,et al.  Location recommendation for location-based social networks , 2010, GIS '10.

[18]  Mohamed F. Mokbel,et al.  Location-based and preference-aware recommendation using sparse geo-social networking data , 2012, SIGSPATIAL/GIS.

[19]  Ling Liu,et al.  From Data Privacy to Location Privacy: Models and Algorithms , 2007, VLDB.

[20]  Dimitrios Gunopulos,et al.  Answering top-k queries using views , 2006, VLDB.

[21]  Abdulmotaleb El-Saddik,et al.  Leveraging personal photos to inferring friendships in social network services , 2012, Expert Syst. Appl..

[22]  Ronald Fagin,et al.  Combining Fuzzy Information from Multiple Systems , 1999, J. Comput. Syst. Sci..

[23]  Michael Moricz,et al.  PYMK: friend recommendation at myspace , 2010, SIGMOD Conference.

[24]  Beng Chin Ooi,et al.  CDAS: A Crowdsourcing Data Analytics System , 2012, Proc. VLDB Endow..

[25]  Moni Naor,et al.  Optimal aggregation algorithms for middleware , 2001, PODS.

[26]  Ihab F. Ilyas,et al.  A survey of top-k query processing techniques in relational database systems , 2008, CSUR.

[27]  Viswanath Poosala Histogram-Based Estimation Techniques in Database Systems , 1997 .

[28]  Yao-Jen Chang,et al.  A General Architecture of Mobile Social Network Services , 2007, 2007 International Conference on Convergence Information Technology (ICCIT 2007).

[29]  Qingming Huang,et al.  Friend recommendation according to appearances on photos , 2009, MM '09.

[30]  John Krumm,et al.  From GPS traces to a routable road map , 2009, GIS.

[31]  Tim Kraska,et al.  CrowdDB: answering queries with crowdsourcing , 2011, SIGMOD '11.

[32]  Gerhard Weikum,et al.  KLEE: A Framework for Distributed Top-k Query Algorithms , 2005, VLDB.

[33]  Flora S. Tsai,et al.  Design and development of a mobile peer-to-peer social networking application , 2009, Expert Syst. Appl..

[34]  Christopher J. C. Burges,et al.  A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.

[35]  D. Reininger,et al.  Web caching framework: analytical models and beyond , 1999, Proceedings 1999 IEEE Workshop on Internet Applications (Cat. No.PR00197).

[36]  Sanjay Ghemawat,et al.  MapReduce: a flexible data processing tool , 2010, CACM.

[37]  Lawrence Mandow,et al.  Multiobjective heuristic search in road maps , 2012, Expert Syst. Appl..

[38]  Wolf-Tilo Balke,et al.  Progressive distributed top-k retrieval in peer-to-peer networks , 2005, 21st International Conference on Data Engineering (ICDE'05).

[39]  Lise Getoor,et al.  Link mining: a survey , 2005, SKDD.

[40]  Joseph M. Hellerstein,et al.  MapReduce Online , 2010, NSDI.

[41]  David D. Jensen,et al.  The case for anomalous link discovery , 2005, SKDD.

[42]  Chris Conley,et al.  Location-Based Services: Time for a Privacy Check-In , 2010 .

[43]  Kwangjin Park,et al.  Location-based grid-index for spatial query processing , 2014, Expert Syst. Appl..

[44]  Padhraic Smyth,et al.  Prediction and ranking algorithms for event-based network data , 2005, SKDD.

[45]  George Varghese,et al.  MobiClique: middleware for mobile social networking , 2009, WOSN '09.

[46]  Shuchuan Lo,et al.  WMR--A Graph-Based Algorithm for Friend Recommendation , 2006, 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06).

[47]  Zhe Wang,et al.  Efficient top-K query calculation in distributed networks , 2004, PODC '04.

[48]  Andrew Zisserman,et al.  Efficient Visual Search of Videos Cast as Text Retrieval , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.