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This paper describes a Web service that automatically parses and extracts data records from Web pages containing structured data. The Web service allows multiple users to share and manage a Web data record extraction task to increase its utility. A recommendation system, based on the probabilistic latency semantic indexing algorithm, enables a user to find potentially interesting content or other...
There are many activities that people prefer/opt out attending and these events are announced for attracting people. An intelligent recommendation system can be used in a social networking site in order to recommend people according to content and collaboration assessment. This study is an effort to recommend events to users within a social networking site. It can be any networking environment. We...
Personalized recommendation systems are becoming increasingly popular with the evolution of the Internet, and collaborative filtering is one of the most important technologies in recommender systems. Such technology recommends items to a customer according to the preference data of similar customers. The main problems of collaborative filtering are about prediction accuracy and data sparsity. To solve...
In this paper, we present COBRAS: a CBR-based peer-to-peer bibliographical reference recommender system. The system allows a group of like-minded people to share their bibliographical data in an implicit and intelligent way. The system associates a software agent with each user. Agents are attributed three main skills: a) detecting the associated user hot topics, b) selecting a subset of peer agents...
Most recommendation methods are "hard-wired" into the system and support only fixed recommendations. The purpose of this demo is to show the expressivity of flexible recommendation workflows, how flexible recommendations can be processed over relational data, and to show flexible recommendations in action through a real system used for course planning.
The use of collaborative filtering (CF) recommenders on the Web is typically done in environments where data is constantly flowing. In this paper we propose an incremental version of item-based CF for implicit binary ratings, and compare it with a non-incremental one, as well as with an incremental user-based approach. We also study the usage of sparse matrices in these algorithms. We observe that...
Recommender systems for e-learning need to consider the specific demands and requirements and to improve the 'educational aspects' for the learners. In this paper, we present a novel hybrid recommender system called RelationalCF, which integrates learners and learning items information into a collaborative filtering framework by using relational distance computation approaches. Our experiments suggest...
Recommendation systems are widely used to cope with the problem of information overload and, consequently, many recommendation methods have been developed for the present recommendation systems, such as content-based, collaborative filtering, Web mining-based and so on. But they are always lack of intelligence, self-adaptiveness and initiative. Aiming at these disadvantages, in this work, a personalized...
Online recommenders are usually referred to those used in e-Commerce websites for suggesting a product or service out of many choices. The core technology implemented behind this type of recommenders includes content analysis, collaborative filtering and some hybrid variants. Since they all have certain strengths and limitations, combining them may be a promising solution provided there is a way of...
The online job market is growing rapidly, with thousands and thousands of jobs matched with job seekers. The major benefits of online job markets are the ability to reach a large number of job seekers at low costs, to provide detailed information online, to take applications and even to conduct tests. Also using intelligent program, resumes can be checked and matches made more quickly. This research...
Accelerated by the rapid deployment of distributed systems and the Internet, online collaboration and information sharing are pervasive in enterprise computing environment. With regard to the requirements of online collaboration and information sharing, authentication information needs flexible manipulation to facilitate federation across trust domains. To achieve identity federation for federated...
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