39616456
Advances in Web and Network Technologies, and Information Management, APWeb/WAIM 2009 International Workshops: WCMT 2009, RTBI 2009, DBIR-ENQOIR 2009, PAIS 2009, Suzhou, China, April 2-4, 2009, Revised Selected Papers
8931794
Speed up semantic search in p2p networks
Peer-to-peer architectures become popular in modern massively distributed systems, which are often in very large scale and contain a huge volume of heterogeneous data. To facilitate the information retrieval process in P2P networks, we consider semantic search approach, where syntax-based queries are shipped to peers based on semantic correlations. Motivated by an interesting experience in Web information retrieval, we propose a novel ontology-based scheme to measure similarity of peer interests accurately and consistently in a decentralized way, and group peers under a scalable hierarchical overlay network. Given queries, our approach either floods them within local peer groups or guides them towards remote groups based on the similarity of interests. Our work overcomes the limitations of the existing P2P hybrid-search approaches by avoiding costly data popularity measurement. Performance evaluation and comparison against baseline algorithms show that our approach provides a better solution for information retrieval in large-scale P2P networks.
9576587
Non-Threshold based Event Detection for 3D Environment Monitoring in Sensor Networks
Event detection is a crucial task for wireless sensor network applications, especially environment monitoring. Existing approaches for event detection are mainly based on some predefined threshold values, and thus are often inaccurate and incapable of capturing complex events. For example, in coal mine monitoring scenarios, gas leakage or water osmosis can hardly be described by the overrun of specified attribute thresholds, but some complex pattern in the full-scale view of the environmental data. To address this issue, we propose a non-threshold based approach for the real 3D sensor monitoring environment. We employ energy-efficient methods to collect a time series of data maps from the sensor network and detect complex events through matching the gathered data to spatio-temporal data patterns. Finally, we conduct trace driven simulations to prove the efficacy and efficiency of this approach on detecting events of complex phenomena from real-life records.
8704395
Summarization Graph Indexing: Beyond Frequent Structure-Based Approach
Graph is an important data structure to model complex structural data, such as chemical compounds, proteins, and XML documents. Among many graph data-based applications, sub-graph search is a key problem, which is defined as given a query Q, retrieving all graphs containing Q as a sub-graph in the graph database. Most existing sub-graph search methods try to filter out false positives (graphs that are not possible in the results) as many as possible by indexing some frequent sub-structures in graph database, such as [20, 22, 4, 23]. However, due to ignoring the relationships between sub-structures, these methods still admit a high percentage of false positives. In this paper, we propose a novel concept, Summarization Graph, which is a complete graph and captures most topology information of the original graph, such as sub-structures and their relationships. Based on Summarization Graphs, we convert the filtering problem into retrieving objects with set-valued attributes. Moreover, we build an efficient signature file-based index to improve the filtering process. We prove theoretically that the pruning power of our method is larger than existing structure-based approaches. Finally, we show by extensive experimental study on real and synthetic data sets that the size of candidate set generated by Summarization Graph-based approach is only about 50% of that left by existing graph indexing methods, and the total response time of our method is reduced 2-10 times.
262231
Monochromatic and bichromatic reverse skyline search over uncertain databases
Reverse skyline queries over uncertain databases have many important applications such as sensor data monitoring and business planning. Due to the existence of uncertainty in many real-world data, answering reverse skyline queries accurately and efficiently over uncertain data has become increasingly important. In this paper, we model the probabilistic reverse skyline query on uncertain data, in both monochromatic and bichromatic cases, and propose effective pruning methods to reduce the search space of query processing. Moreover, efficient query procedures have been presented seamlessly integrating the proposed pruning methods. Extensive experiments have demonstrated the efficiency and effectiveness of our proposed approach with various experimental settings.
7517195
Spotting Significant Changing Subgraphs in Evolving Graphs
Graphs are popularly used to model structural relationships between objects. In many application domains such as social networks, sensor networks and telecommunication, graphs evolve over time. In this paper, we study a new problem of discovering the subgraphs that exhibit significant changes in evolving graphs. This problem is challenging since it is hard to define changing regions that are closely related to the actual changes (i.e., additions/deletions of edges/nodes) in graphs. We formalize the problem, and design an efficient algorithm that is able to identify the changing subgraphs incrementally. Our experimental results on real datasets show that our solution is very efficient and the resultant subgraphs are of high quality.
22828362
Construction of low-density parity-check codes by superposition
This paper presents a superposition method for constructing low-density parity-check (LDPC) codes. Several classes of structured LDPC codes are constructed. Codes in these classes perform well with iterative decoding, and their Tanner graphs have girth at least six.
35643467
A New Virtual Dynamic Dentomaxillofacial System for Analyzing Mandibular Movement, Occlusal Contact, and TMJ Condition
This paper describes a new virtual dynamic dentomaxillofacial system. Mechanical articulators have been used to reproduce mandibular movements and analyze occlusal contacts. With the help of VR and visualization technologies, virtual articulator systems can provide dynamic simulation and quantitative information visualization, enhance the functionality, and extend the system to additional application areas. We integrate mandibular movement simulation, occlusal analysis and TMJ analysis into our system, and design new algorithms to improve the results of analysis. This system is helpful to the education, the research, and the clinic in dentistry. An evaluation is conducted to prove the functionality and usability of the system.
15196694
End-to-end diagnosis of QoS violations with neural network
In this paper, we introduce a novel end-to-end approach to QoS management with respect to the diagnosis of QoS violations. We first use a set of end-to-end flow traffic statistics to describe a QoS violation. Subsequently, neural network techniques are engaged to identify and differentiate QoS violations through classification of the collected statistics. Through experiments, we find that our scheme outperforms traditional rule-based methods which require clear margins of QoS parameters in asserting a QoS violation.
14259203
E-government Web Mining Tool Design and Implementation Based on the Semantic Web
E-government is innovation and change of administrative activities for hundreds of years. This paper proposed a E-government's Web mining method based on the Semantic Web. It first describes the Design and Implementation of the Web spider, tool of colleting network data collection, including the basic structure of the work processes and procedures of the Web spider, the storage structure and form Web spider collected, the network topology discovery algorithms and the major technical difficulties and details of implementation of Web spider. In actual test, the system runs effective and efficient. Finally this paper points out the works that need to improve and upgrade.
37631893
Stereo Vision Based Floor Plane Extraction and Camera Pose Estimation
In this paper, we present a unified approach for floor plane extraction and camera pose estimation. A histogram based method is performed on the reconstructed 3-D points obtained by an onboard video-rate stereo vision system to extract candidate points of the floor plane and determine the pose of vision system simultaneously. The obstacle area is easily localized given the floor plane region. In order to improve reliability and accuracy of camera pose estimation results, the Least Median of Squares (LMedS) based fitting method is applied to estimate the floor plane parameters with the extracted candidate points. The precise pose of the onboard stereo vision system is directly acquired related to the floor plane parameters. Experimental results in real indoor environments are discussed and show the good performance.