Representation of rules for relevant recommendations to online social networks users

In our prior work, we identified rules for use in recommendation algorithms on Online Social Network (OSN) in order to increase the relevance of content suggested to a user. The resulting recommendation algorithms filter out and prioritize event types for OSN users (such as photo posts by friends, status posts, shared content, etc.), and are thereby intended to reduce information overload. This paper proposes a representation of these rules in a requirements model of a OSN. This is interesting, because recommendation rules influence user behavior, which in turn influences future requirements. If there is a recommendation algorithm, then its behavior should be represented also in requirements models of the system. The paper makes two contributions. We define requirements that OSNs should satisfy in order to produce relevant recommendations of event types to users. We investigate whether an existing requirements modeling language (namely, i-star) can be used to model these requirements.

[1]  David Carmel,et al.  Social media recommendation based on people and tags , 2010, SIGIR.

[2]  Michael J. Muller,et al.  Make new friends, but keep the old: recommending people on social networking sites , 2009, CHI.

[3]  Alireza Sahami Shirazi,et al.  Large-scale assessment of mobile notifications , 2014, CHI.

[4]  Sung-Bong Yang,et al.  An Improved Recommendation Algorithm in Collaborative Filtering , 2002, EC-Web.

[5]  Xing Xie,et al.  Potential Friend Recommendation in Online Social Network , 2010, 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing.

[6]  Christos Faloutsos,et al.  TANGENT: a novel, 'Surprise me', recommendation algorithm , 2009, KDD.

[7]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[8]  Eric S. K. Yu,et al.  Towards modelling and reasoning support for early-phase requirements engineering , 1997, Proceedings of ISRE '97: 3rd IEEE International Symposium on Requirements Engineering.

[9]  Martin Pielot,et al.  An in-situ study of mobile phone notifications , 2014, MobileHCI '14.

[10]  Tim Weninger,et al.  Collaborative and Structural Recommendation of Friends using Weblog-based Social Network Analysis , 2006, AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs.

[11]  Yao Zhao,et al.  A Collaborative Filtering Recommendation Algorithm Based on User Interest Change and Trust Evaluation , 2010, J. Digit. Content Technol. its Appl..

[12]  M. Miyazaki,et al.  Recommendation algorithm focused on individual viewpoints , 2005, Second IEEE Consumer Communications and Networking Conference, 2005. CCNC. 2005.

[13]  Eric Yu,et al.  Modeling Strategic Relationships for Process Reengineering , 1995, Social Modeling for Requirements Engineering.

[14]  Ioannis Konstas,et al.  On social networks and collaborative recommendation , 2009, SIGIR.

[15]  Fahim Kawsar,et al.  The myth of subtle notifications , 2014, UbiComp Adjunct.

[16]  Ido Guy,et al.  Do you know?: recommending people to invite into your social network , 2009, IUI.

[17]  Yo-Sub Han,et al.  A movie recommendation algorithm based on genre correlations , 2012, Expert Syst. Appl..