Companies of the same industry sector are often connected into a corporate network for collaboration purposes. Each company maintains its own site and selectively shares a portion of its business data with the others. The corporate network is often used for sharing information among the participating companies and facilitating collaboration in a certain industry sector […]
DQF-A NOVEL DYNAMIC QUERY FORMS FOR DATABASE QUERIES
Traditional query forms are designed and predefined by developers or DBA in various information management systems. Traditional predefined query forms are not able to satisfy various ad-hoc queries from users on those databases. This abstract proposes DQF, a novel database query form interface, which is able to dynamically generate query forms. The essence of DQF […]
COMMTRUST-MINING E-COMMERCE FEEDBACK COMMENTS
Accurate trust evaluation is crucial for the success of e-commerce systems. Reputation reporting systems have been implemented in e-commerce systems such as eBay and Amazon (for third-party sellers), where overall reputation scores for sellers are computed by aggregating feedback ratings. Reputation-based trust models are widely used in e-commerce applications, and feedback ratings are aggregated to […]
DATABASE QUERIES IN DYNAMIC QUERY FORMS
In this abstract, we propose a Dynamic Query Form system: DQF, a query interface which is capable of dynamically generating query forms for users. Different from traditional document retrieval, users in database retrieval are often willing to perform many rounds of actions (i.e., refining query conditions) before identifying the final candidates. The essence of DQF […]
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. […]
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 […]
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, […]
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 […]
PUBLIC SENTIMENT VARIATIONS ANALYZING ON TWITTER
Twitter has become a social site where millions of users can exchange their opinion. Sentiment analysis on Twitter data has provided an economical and effective way to expose public opinion timely, which is critical for decision making in various domains. In this work, we move one step further to interpret sentiment variations. We observed that […]
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