The emergence of mobile devices with fast Internet connectivity and geo-positioning capabilities has le d to a revolution in customized location – based services (LBS) , where users are enabled to access information about points of interest (POI ) that are relevant to their interests and are also close to their geographical coordinates. Pro b- […]
Archives for March 2015
PRIVATE MATCHING PROTOCOLS BASED ON ASYMMETRIC SOCIAL PROXIMITY FOR ONLINE SOCIAL NETWORKS
In OSNs and Mobile Social Networks (MSNs), many distributed solutions to privately finding the social proximity between two users have been proposed in this abstract. The most common way of determining friendship between two people is through profile matching, i.e. finding out if they have common profile attributes, like interests, symptoms, or some other social […]
ONLINE SOCIAL NETWORKS USING ASYMMETRIC SOCIAL PROXIMITY BASED PRIVATE MATCHING PROTOCOLS
Online Social Networks have redefined the way people interact with existing friends, and more importantly, make new friends. In particular, people can now explore potential friendships via OSNs, by looking for common interests, friends, and symptoms, close geographic proximity, etc., between each other. In this abstract, we leverage community structures to redefine the OSN model […]
COMBINING USER INTEREST AND SOCIAL CIRCLE WITH PERSONALIZED RECOMMENDATION
Recommender system (RS) has been successfully exploited to solve information overload. In E-Commerce, like Amazon, it is important to handling mass scale of information, such as recommending user preferred items and products. With the advent and popularity of social network, more and more users like to share their experiences, such as ratings, reviews, and blogs. […]
PRIVACY-PRESERVING ALGORITHMS FOR DETERMINING AN OPTIMAL MEETING LOCATION FOR MOBILE DEVICES
Privacy of a user’s location or location preferences, with respect to other users and the third-party service provider, is a critical concern in such location-sharing-based applications. Equipped with state-of-the-art smart phones and mobile devices, today’s highly interconnected urban population is increasingly dependent on these gadgets to organize and plan their daily lives. These applications often […]
PERSONALIZED RECOMMENDER SYSTEM COMBINING USER INTEREST AND SOCIAL CIRCLE
In this abstract, three social factors, personal interest, inter-personal interest similarity, and interpersonal influence, fuse into a unified personalized recommendation model based on probabilistic matrix factorization. The personality is denoted by user-item relevance of user interest to the topic of item. To embody the effect of user’s personality, we mine the topic of item based […]
OPTIMAL MEETING LOCATION DETERMINATION ON MOBILE DEVICES FOR PRIVACY
Smartphone technology in urban communities has enabled mobile users to utilize context-aware services on their devices. Service providers take advantage of this dynamic and ever-growing technology landscape by proposing innovative context-dependent services for mobile subscribers. Location-based Services (LBS), for example, are used by millions of mobile subscribers every day to obtain location-specific information. In this […]
RELATIONAL DBMSS WITH SHORTEST PATH COMPUTING
Graph search is highly needed in applications over graphs. Specifically, graph search seeks a sub-graph(s) meeting the specific purposes, such as the shortest path between two nodes, the minimal spanning tree, the salesman traveling path, and the like. We also observe that these graphs are always exceedingly large and keep growing at a fast rate. […]
SHORTEST PATH DISCOVERY FOR EFFICIENT RELATIONAL APPROACHES TO GRAPH SEARCH QUERIES
Relational Database (RDB) provides a promising infra-structure to support graph search. After more than 40 years of development, RDB is mature and stable enough, and plays a key role in information systems. This abstract takes the shortest path discovery to study efficient relational approaches to graph search queries. We first abstract three enhanced relational operators, […]
TOF-A GENERAL TRANSFORMATION-BASED OPTIMIZATION FRAMEWORK FOR WORKFLOWS IN THE CLOUD
A workflow management system should balance the cost and performance. Thus, performance and (monetary) cost optimizations have recently become a hot research topic for workflows in the cloud. However, we find that most existing studies adopt ad hoc optimization strategies, which fail to capture the key optimization opportunities for different workloads and cloud offerings (e.g., […]