16665207
RCCtrust: A Combined Trust Model for Electronic Community
Previous trust models are mainly focused on reputational mechanism based on explicit trust ratings. However, the large amount of user-generated content and community context published on Web is often ignored. Without enough information, there are several problems with previous trust models: first, they cannot determine in which field one user trusts in another, so many models assume that trust exists in all fields. Second some models are not able to delineate the variation of trust scales, therefore they regard each user trusts all his friends to the same extent. Third, since these models only focus on explicit trust ratings, so the trust matrix is very sparse. To solve these problems, we present RCCtrust – a trust model which combines Reputation-, Content- and Context-based mechanisms to provide more accurate, fine-grained and efficient trust management for the electronic community. We extract trust-related information from user-generated content and community context from Web to extend reputation-based trust models. We introduce role-based and behavior-based reasoning functionalities to infer users' interests and category-specific trust relationships. Following the study in sociology, RCCtrust exploits similarities between pairs of users to depict differentiated trust scales. The experimental results show that RCCtrust outperforms pure user similarity method and linear decay trust-aware technique in both accuracy and coverage for a Recommender System.
45332140
Semantic Web Development for Traditional Chinese Medicine
The present invention relates to an improved tool grinding mechanism for grinding single point diamond cutting tools to precise roundness and radius specifications. The present invention utilizes a tool holder which is longitudinally displaced with respect to the remainder of the grinding system due to contact of the tool with the grinding surface with this displacement being monitored so that any variation in the grinding of the cutting surface such as caused by crystal orientation or tool thickness may be compensated for during the grinding operation to assure the attainment of the desired cutting tool face specifications.
12804860
A Novel 3-DOF HIP Exoskeleton for Kinematically Establishing Animal Model of Avascular Necrosis of the Femoral Head
This paper outlines a detailed description of the design on a 3-DOF hip robotic device for kinematically establishing animal model of avascular necrosis (AVN) of the femoral head. In order to realize the hip extension/flexion and abduction/adduction movements of rabbit subjects, a novel 2-DOF hip motion apparatus based on a pair of cardan joints is investigated. 2 electric grounded motors are used to drive rabbits passively in terms of predefined trajectories repeatedly with an additional periodical impact loading on the femoral head during motions. It is ideal to simulate usual forceful and repeated actions in sports, such as gymnastics and acrobatics, and initiated a new way to establish animal femoral head AVN models by means of kinematically simulating the real motion procedure rather than traditional medical or physiological operation method. With sets of experiments, the characterization of the exoskeleton system is discussed.
18873066
Extending Online Travel Agency with Adaptive Reservations
Current online ticket booking systems either do not allow customers to reserve a ticket with a locked price, or grant a fixed reservation timespan, typically 24 hours. The former often leads to false availability: when a customer decides to purchase a ticket after a few queries, she finds that either the ticket is no longer available or the price has hiked up. The latter, on the other hand, may result in unnecessary holdback: a customer cannot purchase a ticket because someone else is holding it, who then cancels the reservation after an excessively long period of time. False availability and holdback routinely lead to loss of revenues, credibility and above all, customers. To rectify these problems, this paper introduces a transaction model for e-ticket systems to support a reservation functionality: customers can reserve tickets with a locked price, for a timespan that is determined by the demands on the tickets, rather than being fixed for all kinds of the tickets. We propose a method for implementing the model, based on hypothetical queries and triggers. We also show how to adjust the reservation timespan w.r.t. demands. We experimentally verify that our model and methods effectively reduce both false availability and holdback rates. These yield a practical approach to improving not only e-ticket systems but also other e-commerce systems.
17285338
A reputation-chain trust model for the semantic Web
Trust plays a central role for efficient and secure interactions on the semantic Web. Nowadays, more and more research has focused on this topic. In this paper, we introduce RCSW, a reputation-chain trust model for the semantic Web. We illustrate the basic definitions and mechanisms of RCSW and present the algorithm to calculate trust ratings through the chain of the trust network. RCSW incorporates pairwise trust values and reliable factors of acquaintances and constructs an edge-weighted graph to calculate trust ratings. We also define classes of trust functions to allow users to individualize their trust calculation. Our proposed model can deal with trust management effectively and can quickly adapt to the changing environment.
11913920
Content-Based Trust Mechanism for E-commerce Systems
Previous trust mechanisms are mainly focused on reputational models based on explicit trust ratings. However, the large amount of system-provided and user-generated content published on Web is often ignored. These information is very important for providing more accurate, fine-grained and efficient trust management. In this paper, we propose a content-based trust mechanism and introduce trust reasoning functionalities which can infer a user's interests and expertise. We present a new method to calculate user similarity based on their feedbacks on reviews to reduce data sparseness of User Similarity matrix. We pinpoint several characteristics of trust which have been overlooked previously: trust is field-dependant, similarity-sensitive, personalized and etc. we differ various trust levels between pairs of users to support more accurate and efficient trust calculation. Although we choose Epinions as our targeted application, the mechanism proposed in this paper are also applicable to other e-commerce systems.
16416654
Topic Tracking Based on Keywords Dependency Profile
Topic tracking is an important task of Topic Detection and Tracking (TDT). Its purpose is to detect stories, from a stream of news, related to known topics. Each topic is "known" by its association with several sample stories that discuss it. In this paper, we propose a new method to build the keywords dependency profile (KDP) of each story and track topic basing on similarity between the profiles of topic and story. In this method, keywords of a story are selected by document summarization technology. The KDP is built by keywords co-occurrence frequency in the same sentences of the story. We demonstrate this profile can describe the core events in a story accurately. Experiments on the mandarin resource of TDT4 and TDT5 show topic tracking system basing on KDP improves the performance by 13.25% on training dataset and 7.49% on testing dataset comparing to baseline.
28042339
Chinese Abbreviation-Definition Identification: A SVM Approach Using Context Information
As a special form of unknown words, Chinese abbreviations represent significant problems for Chinese text processing. The goal of this study is to automatically find the definition for a Chinese abbreviation in the context where both the abbreviation and its definition occur, enforcing the constraint of one sense per discourse for an abbreviation. First, the candidate abbreviation-definition pairs are collected, and then a SVM approach using context information is employed to classify candidate abbreviation-definition pairs so that the pairs can be identified. The performance of the approach is evaluated on a manually annotated test corpus, and is also compared with two other machine learning approaches: Maximum Entropy and Decision Tree. Experimental results show that our approach reaches a good performance.
44740953
Non-Uniform "Fat-Meshes" for Chip Multiprocessors
This paper studies the traffic hot spots of mesh networks in the context of chip multiprocessors. To mitigate these effects, this paper describes a non-uniform fat-mesh extension to mesh networks, which are popular for chip multiprocessors. The fat-mesh is inspired by the fat-tree and dedicates additional links for connections with heavy traffic (e.g. near the center) with fewer links for lighter traffic (e.g. near the periphery). Two fat-mesh schemes are studied based on the traffic requirements of chip multiprocessors using dimensional ordered XY routing and a randomized XY-YX routing algorithms, respectively. Analytical fat-mesh models are constructed by theoretically presenting the expressions for the traffic requirements of personalized all-to-all traffic for both the raw message numbers and their normalized equivalents. We demonstrate how traffic scales for a traditional mesh compared to a non-uniform fat mesh. Simulation results demonstrate that using same number of physical links the non-uniform fat-mesh can achieve better performance than a uniform fat-mesh mesh using both synthetic traffic patterns and splash-2 benchmark traces.
37152915
Image Disorientation Auto-Recovery
Automatically detecting and correcting disoriented image frames in a content-related image sequence is a problem that must be addressed in many image and video applications. In this paper, we give a robust feature-based algorithm to efficiently detect and adjust the disorientation of images. Keyword image orientation, crop, Robert edge detection, line feature, Hough transformation.
17429523
A Novel Trust-based Cooperative Node Selection Scheme in Wireless Sensor Networks
For communication between the cluster head node (CHN) and the distant data fusion center (DFC) with the cooperation of intra-cluster nodes in wireless sensor networks (WSNs), reliable handling of packets by the cooperative node (CN) is difficult to ensure. In this paper, we propose a novel CN selection scheme based on trust for WSNs. This scheme can choose one of high trust nodes to assist in the transmission of CHN, which aims to improve the transmission performance over cooperative communication in the presence of potential malicious nodes. First, we establish a trust model to improve the reliability of transmission by CN in WSNs, which is based on both the direct trust and the indirect trust of nodes. Then the CHN selects a node based on the proposed trust model to aid the CHN in transmission. Simulation results show that the proposed scheme can mitigate the impact of the potential malicious nodes on transmission performance and the simulation results also demonstrate the efficiency of the proposed scheme.