Harnessing Facebook for the Evaluation of Recommender Systems based on Physical Copresence
نویسندگان
چکیده
Various mobile social applications have proposed the use of ad-hoc network connectivity as a means of detecting user encounters and shared social contexts. These applications range from simple opportunistic information sharing to techniques for collaborative filtering in mobile settings. However, it can be difficult and costly to test the underlying assumption that repeated physical copresence can be used as a measure of user similarity. We have therefore developed a framework that allows existing online social platforms such as Facebook to be coupled with simple, standard mobile applications in order to test such hypotheses. The central idea is to map the physical copresence of users to connections in virtual social networks and then exploit the rich support for developing pluggable applications to measure user similarity within these networks.
منابع مشابه
Evaluation of recommender systems: A multi-criteria decision making approach
The evaluation and selection of recommender systems is a difficult decision making process. This difficulty is partially due to the large diversity of published evaluation criteria in addition to lack of standardized methods of evaluation. As such, a systematic methodology is needed that explicitly considers multiple, possibly conflicting metrics and assists decision makers to evaluate and find...
متن کاملA Review of Spatial Factor Modeling Techniques in Recommending Point of Interest Using Location-based Social Network Information
The rapid growth of mobile phone technology and its combination with various technologies like GPS has added location context to social networks and has led to the formation of location-based social networks. In social networking sites, recommender systems are used to recommend points of interest (POIs) to users. Traditional recommender systems, such as film and book recommendations, have a lon...
متن کاملProviding a model based on Recommender systems for hospital services (Case: Shariati Hospital of Tehran)
Background and objectives: In the increasingly competitive market of the healthcare industry, the organizations providing health care services are highly in need of systems that will enable them to meet their clients' needs in order to achieve a high degree of patient satisfaction. To this end, health managers need to identify the factors affecting patient satisfaction focus. T...
متن کاملAn Effective Algorithm in a Recommender System Based on a Combination of Imperialist Competitive and Firey Algorithms
With the rapid expansion of the information on the Internet, recommender systems play an important role in terms of trade and research. Recommender systems try to guess the user's way of thinking, using the in-formation of user's behavior or similar users and their views, to discover and then propose a product which is the most appropriate and closest product of user's interest. In the past dec...
متن کاملMerging Similarity and Trust Based Social Networks to Enhance the Accuracy of Trust-Aware Recommender Systems
In recent years, collaborative filtering (CF) methods are important and widely accepted techniques are available for recommender systems. One of these techniques is user based that produces useful recommendations based on the similarity by the ratings of likeminded users. However, these systems suffer from several inherent shortcomings such as data sparsity and cold start problems. With the dev...
متن کامل