Deren Chen

Generating digital signatures on mobile devices

With the explosion of the mobile communication market, more and more handheld devices act as clients in the Internet. People use these devices to purchase books, play games, receive emails, etc. For protecting privacies, such applications should integrate digital signature schemes. Since handheld devices have poor computational capabilities and limited battery life, traditional computation intensive digital signature protocols that are based on asymmetric cryptographic algorithms are not suitable for mobile devices. We propose a server based signature (SBS) scheme for mobile devices. Besides achieving the same security level of the traditional digital signature protocols, the SBS scheme also: 1) reduces the computation complexity on the mobile devices; 2) reduces the communication consumption between signer and verifier. Application results show that our scheme is very useful for mobile communication systems.

A hybrid approach for movie recommendation via tags and ratings

A hybrid recommendation approach for movies via tags and ratings was proposed.Social tags were reconstructed according to user preference based on content annotation.Our model improved the ability of fusion by applying the potential aspects.Our hybrid method significantly outperforms comparative recommendation approaches. Selecting a movie often requires users to perform numerous operations when faced with vast resources from online movie platforms. Personalized recommendation services can effectively solve this problem by using annotating information from users. However, such current services are less accurate than expected because of their lack of comprehensive consideration for annotation. Thus, in this study, we propose a hybrid movie recommendation approach using tags and ratings. We built this model through the following processes. First, we constructed social movie networks and a preference-topic model. Then, we extracted, normalized, and reconditioned the social tags according to user preference based on social content annotation. Finally, we enhanced the recommendation model by using supplementary information based on user historical ratings. This model aims to improve fusion ability by applying the potential effect of two aspects generated by users. One aspect is the personalized scoring system and the singular value decomposition algorithm, the other aspect is the tag annotation system and topic model. Experimental results show that the proposed method significantly outperforms three categories of recommendation approaches, namely, user-based collaborative filtering (CF), model-based CF, and topic model based CF.

URL Rule Based Focused Crawler

Vertical search engines use focused crawlers as their key component and develop some specific algorithms to select Web pages relevant to some pre-defined set of topics. Therefore, how to effectively build up a semantic pattern for specific topics is extremely important to such search engines. In this paper we propose an UBFC (URL rule based focused crawler) algorithm based on a double-crawler framework (an experimental crawler and a focused crawler). The kernel of our UBFC is an URL regular expression learner, which is used to automatically learn and generalize the regular expressions of URLs of the sample Web pages. The so generated URL regular expressions are used to direct the UBFC to work. Using UBFC, we developed a Nutch based focused crawler for hardwaretoday.com and get an excellent result. To evaluate the UBFC, we conduct some experiments to make an analysis through comparison with two proposed methods, the BFSC (breadth first search crawler) and BLFC (baseline focused crawler).

Research of architecture for grid manufacturing

Architecture for grid manufacturing system was provided. The evolution of manufacturing mode and the naissance of grid manufacturing were analyzed, and the typical architecture for grid was introduced, they are the layered sandglass structure and the open grid service architecture (OGSA). Then we analyzed the scheme of grid manufacturing for Shaoxing spinning region, based on which, architecture for grid manufacturing system was proposed. The manufacturing grid architecture absorbed the five-level framework of grid and the grid services idea in OGSA, and integrated many supporting toolboxes and protocols of Globus, which is a helpful exploration to the development of grid manufacturing system.

Image-Based Walkthrough over Internet on Mobile Devices

Real-time rendering of complex 3D scene on mobile devices is a challenging task. The main reason is that mobile devices have limited computational capabilities and are lack of powerful 3D graphics hardware support. In this paper, we propose an Image-Based Rendering (IBR) system for mobile devices to visualize real-world or synthetic scenes in network environment. Our system uses server for computing the required image segments of pre-captured panoramic video, and transmitting them to client. After receiving data, mobile client carries out rendering using simple image warping. The rendering process needs less computational power and is insensitive to the scene’s complexity. A rate-control scheme is designed for efficient use of network bandwidth for handling network congestion. Pre-fetching and cache management are also considered on client and server sides for efficient memory use and reducing transmission request. With this client-server architecture and local rendering scheme, interactive exploration of 3D scene on mobile devices becomes possible. Experimental results show that our system can achieve acceptable rendering speed on common mobile devices.

Recommender System Based on Social Trust Relationships

The development of social network has increased the importance of social recommendation. However, social recommender systems have only recently been given research attention. Social relationships between users, especially trust relationships, can facilitate the design of social recommender systems. Such systems are based on the idea that users linked by a social network tend to share similar interests. Existing recommender approaches based on social trust relationships do not fully utilize such relationships and thus have low prediction accuracy or slow convergence speed. We propose a factor analysis approach that explicitly and implicitly uses social trust relationships simultaneously to overcome this limitation and fully utilize social trust relationships. Our approach combines the advantages of the existing two approaches, social recommendation using probabilistic matrix factorization and learning to recommend with social trust ensemble. Based on Epinions data sets, our approach has both significantly higher prediction accuracy and convergence speed than traditional collaborative filtering technology and state-of-the-art trust-based recommendation approaches.

Policy-Based Web Service Selection in Context Sensitive Environment

Web service selection is a key issue in the service-oriented computing. Generally, Web services are provided with different QoS values, so they can be selected dynamically in service composition process. However, the conventional context free QoS selection model does not consider the context sensitive constraints and the changeability of QoS values. This paper proposes a policy-based context sensitive QoS model to effectively calculate QoS values and select web services. By introducing context to the QoS model, web service composition can be used widely and flexibly in the real world business.

Intelligent agent-based scheduling mechanism for grid service

Load balancing and fault tolerance are two key concerns when developing distributed computing applications. The emergence of grid computing environments extends this problem. Based on distributed scheduling architecture, a grid service oriented scheduling model is proposed to enable load balancing in this paper. In this model, the functionalities are characterized by fault tolerance, and implemented by applying intelligent agent technology. Degree of credit is introduced to make that a decision of grid service selection, service instance selection/migration and service instance redundancy, context agents are responsible for sensing the context of grid, and balance agents are enforced to automatically serve the scheduler for dynamic load adjustment and service-level fault tolerance. Between agents, information exchange is conducted via an agent communication language.

Trust Based Service Selection in Service Oriented Environment

In a service-oriented environment, it is inevitable and indeed quite common to deal with web services, whose reliability is unknown to the users. The reputation system is a popular technique currently used for providing a global quality score of a service provider to requesters. However, such global information is far from sufficient for service requesters to choose the most qualified services. In order to tackle this problem, the authors present a trust based architecture containing a computational trust model for quantifying and comparing the trustworthiness of services. In this trust model, they firstly construct a network based on the direct trust relations between participants and rating similarity in service oriented environments, then propose an algorithm for propagating trust in the social network based environment which can produce personalized trust information for a specific service requester, and finally implement the trust model and simulate various malicious behaviors in not only dense but also sparse networks which can verify the attack-resistant and robustness of the proposed approach. The experiment results also demonstrate the feasibility and benefit of the approach.

Automatic forecasting agent for e-commerce applications

Forecasting has been playing an important role in many industries such as marketing, financial planning, and production control. This paper firstly gives a brief review of time series forecasting techniques, particularly covers moving averages model and exponential smoothing mode. We, then applies an illustrative example to these techniques with actual data and compares four different results by introducing the concept of mean square error (MSE) and mean absolute error (MAE). The technique can be used in an implementation of autonomous agent, which can be used in any e-commerce as a back end computation mechanism for applications. Finally wet conclude by summarizing the results and discussing avenues for future research.