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., […]
PRODUCT ASPECT RANKING FOR AUTOMATICALLY IDENTIFY THE IMPORTANT ASPECTS OF PRODUCTS FROM NUMEROUS CONSUMER REVIEWS
In this abstract propose a product aspect ranking framework to automatically identify the important aspects of products from numerous consumer reviews. It develop a probabilistic aspect ranking algorithm to infer the importance of various aspects by simultaneously exploiting aspect frequency and the influence of consumers’ opinions given to each aspect over their overall opinions on […]
WORKFLOWS IN THE CLOUD USING TRANSFORMATION-BASED MONETARY COST OPTIMIZATIONS
This abstract proposes ToF, a general transformation-based optimization framework for workflows in the cloud. Specifically, ToF formulates six basic workflow transformation operations. An arbitrary performance and cost optimization process can be represented as a transformation plan (i.e., a sequence of basic transformation operations). All transformations form a huge optimization space. We further develop a cost […]
PROBABILISTIC ASPECT RANKING ALGORITHM FOR PRODUCT ASPECT RANKING AND ITS APPLICATIONS
Product aspect ranking is beneficial to a wide range of real-world applications. The important product aspects are identified based on two observations: 1) the important aspects are usually commented on by a large number of consumers and 2) consumer opinions on the important aspects greatly influence their overall opinions on the product. In particular, given […]
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