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The increasing volume of spam has become a serious threat not only to the Internet, but also to the society. However, it's a great challenge to discover the spam from the Internet effectively and efficiently. Content-based filtering is one of the mainstream methods to solve the problem. This paper proposed a content based spam topic detection strategy through keyword extraction. In particular, spam...
With the development of Internet, the increasing volume of information posted on micro-blogging sites like Twitter necessitates the need for efficient information filtering. In conventional text classification problems, it is assumed that the feature vectors extracted from the available documents are sufficient to learn good classifiers. However, this conventional approach is not likely to work for...
In this paper, we develop a novel framework that attempts to reduce network traffic for error-bounded data collection in wireless sensor networks. In many sensor applications, it is acceptable that the monitoring results evaluated based on collected data might deviate from the exact results; as long as the error is bounded by a certain threshold. One well-known technique for error-bounded data collection...
For the popular DIV page layout in Web Pages, this paper presents a method based on the position of DIV to extract main text from the body of Web pages by reconstructing, remaining atomic DIV and analyzing DIV position. Experiments showed that the accuracy rate of extraction can reach more than 90%, with a high versatility and accuracy.
Collaborative Filtering (CF) algorithms are widely used in a lot of recommender systems, however, the computational complexity of CF is high thus hinder their use in large scale systems. In this paper, we implement user-based CF algorithm on a cloud computing platform, namely Hadoop, to solve the scalability problem of CF. Experimental results show that a simple method that partition users into groups...
Based on the analysis of the current hybrid recommender systems, this paper proposes a new recommender system framework to overcome the disadvantage of these hybridization technologies. In the new system, various Web personalized recommending methods are integrated into a market model. It is capable of producing recommendations for the unregistered users. And a finely reasonable auction process is...
The paper proposed the importance of document filtration system for scientific and technological personnel, and then gave a solution of filtering system at the perspective of software architecture. Finally, this paper provided a complete implementation of filtering system base on the analysis and the design, proving the feasibility of this architecture and our framework.
Collaborative filtering is one of the most successful technologies in recommender systems, and widely used in many personalized recommender areas with the development of Internet, such as e-commerce, digital library and so on. The K-nearest neighbor method is a popular way for the collaborative filtering realizations. Its key technique is to find k nearest neighbors for a given user to predict his...
Event-based self-adaptation of user interface (UI) is introduced in this paper as an approach to solving problems in current static and dynamic UI approaches. Our approach does not require extra information about the user or the context, but uses events which can be gathered easily. Our approach adopts the concept of an agent to make externalization of UI adaptation, that is, no need to make intensive...
This paper presents a scalable and adaptive decentralized metadata lookup scheme for ultra large-scale file systems (ges Petabytes or even Exabytes). Our scheme logically organizes metadata servers (MDS) into a multi-layered query hierarchy and exploits grouped bloom filters to efficiently route metadata requests to desired MDS through the hierarchy. This metadata lookup scheme can be executed at...
A scalar median filter algorithm for color image based on the rotation of color space is presented in this paper. It converts the vector median filter to simpler scalar median filters by rotating color space. The rotation of color space can make the majority noise pixels satisfying scalar median filter conditions at each scalar and being filtered. This method is iterative, and the rotation matrix...
In wireless sensor networks, filters, which suppress data update reports within predefined error bounds, effectively reduce the traffic volume for continuous data collection. All prior filter designs, however, are stationary in the sense that each filter is attached to a specific sensor node and remains stationary over its lifetime. In this paper, we propose mobile filter, a novel design that explores...
Providing range query as basic network services has received much research attention recently. Range query can exhibit all items located within a certain range. Previous approaches to represent and query items, such as distributed hash tables (DHT) or R-tree structures, use too much storage space to store and maintain items to achieve exact query results. Corresponding structures cannot effectively...
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