An increasing number of databases have become Web accessible through HTML form-based search interfaces, which is so-called deep Web. For full utilization of deep Web resources and improving Web intelligence, which is ...
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An increasing number of databases have become Web accessible through HTML form-based search interfaces, which is so-called deep Web. For full utilization of deep Web resources and improving Web intelligence, which is essential for many applications such as deep Web data collection and comparison shopping, they need to be extracted out and assigned meaningful labels. In this paper, we present a synchronous-annotation approach that introduce domain ontology as a global schema ordered by Web databases to the annotation process. We combine ontology, interface schema and result schema and adopt the strategy of query ontology instance to implement annotation. In order to verify the effectiveness of the method proposed in this paper, we test on a number of different areas of Web databases. The experimental results indicate that the proposed approach is more effective than existing approaches.
A lot of high quality and wealthy data are hidden in backend database and search engines can not index this page, which is called Deep Web. It is mostly accessible through query interfaces. SDWS, a semantic search eng...
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ISBN:
(纸本)9781424430536;9780769531519
A lot of high quality and wealthy data are hidden in backend database and search engines can not index this page, which is called Deep Web. It is mostly accessible through query interfaces. SDWS, a semantic search engine for Deep Web is presented. We are studying and implementing semantic Web technology to the each process of Deep Web information integrated, and expertise in Deep Web discovering, annotating query results and integrating information. The novel approach promise better access to Deep Web.
Traditional text classification model uses statistical methods to obtain features. But in the aspect of discrimination domain and non-domain text category, domain knowledge relations haven't been taken account of ...
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Traditional text classification model uses statistical methods to obtain features. But in the aspect of discrimination domain and non-domain text category, domain knowledge relations haven't been taken account of in these methods. A domain text classification model was presented in this paper. This model used the support vector machine learning algorithm, gained domain classification feature words through statistic and union domain words, structured domain classification feature space. With the help of domain knowledge relations, computed relevance between domain concepts, got domain classification feature weight. Finally domain text classification was realized. An experiment in the Yunnan tourism domain was carried on to confirm that domain knowledge relations have a good influence on the domain text classification. The classification accuracy rate has been increased 0.04 than improved TFIDF method.
Based on least squares support vector machines (LS-SVM) and Wavelet Transform theory, a novel approach for short-term power load forecasting is presented. The historical time series is decomposed by wavelet, so the ap...
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Based on least squares support vector machines (LS-SVM) and Wavelet Transform theory, a novel approach for short-term power load forecasting is presented. The historical time series is decomposed by wavelet, so the approximate part and several detail parts are obtained. Then the results of Wavelet Transform are predicted by a separate LS-SVM predictor. The new forecast model combines the advantage of WT with LS-SVM. Compared with other predictors, this forecast model has greater generalizing ability and higher accuracy.
Supply chain management is the major field for RFID application. However, little work has been conducted to address the security issues in this context. Existing RFID solutions cannot be applied directly in this field...
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Supply chain management is the major field for RFID application. However, little work has been conducted to address the security issues in this context. Existing RFID solutions cannot be applied directly in this field because of a set of special RFID security requirements to be addressed for supply chain management. The major contribution of this paper is to identify the unique set of security requirements for secure RFID communications in supply chains, propose a universally composable model that satisfies the security requirements, and design a lightweight protocol that realizes the universally composable model. This paper further defines the security requirement of unlinkability, and classifies the typical RFID protocols according to the security requirements.
Due to the thrive of networking multimedia, artificial intelligence and embedded system, video surveillance system is evolved from computer-based to embedded-based. This paper presents an intelligent multimedia survei...
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Due to the thrive of networking multimedia, artificial intelligence and embedded system, video surveillance system is evolved from computer-based to embedded-based. This paper presents an intelligent multimedia surveillance system based on embedded video server. Design and implementation issues of this surveillance system are discussed including system architecture, hardware design and software framework. Moreover, practical applications show that our framework can suitable for commercial applications.
A new robust watermarking 3D mesh model algorithm is presented in this paper. We embed two different watermarks into a 3D mesh. One of the two watermarks is based on feature information and another is embedded by Niel...
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A new robust watermarking 3D mesh model algorithm is presented in this paper. We embed two different watermarks into a 3D mesh. One of the two watermarks is based on feature information and another is embedded by Nielson norm. The two watermarks do not disturb each other. Since the algorithm is blind, it does not need the original model during extraction. The algorithm is applied to many mesh models. These experiments show that the watermarking scheme not only can keep original mesh feature information but also can resist some attacks, such as affine transformation, noising and cropping.
Garbage collection is a memory management mechanism for automatically reclaiming garbage objects in memory. It can effectively relieve the programmers' burden and optimize the design of programs. Currently many ga...
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Garbage collection is a memory management mechanism for automatically reclaiming garbage objects in memory. It can effectively relieve the programmers' burden and optimize the design of programs. Currently many garbage collection methods for distributed systems have been put forth as the distributed systems are more and more popular. Relaxed consistency model is a very important kind of memory consistency model in distributed system, but it is inefficiently to perform garbage collection in the Distributed shared memory system (DSM) on relaxed memory model with traditional methods. This article proposes a trace-based garbage collection algorithm for DSM system based on relaxed memory model. Our algorithm notes the references among active objects of every node in DSM system, which makes the application process and the collection process able to execute concurrently. And it makes use of the relaxed consistency model's features to reduce communication cost and response delay. Furthermore, the use of two tables insures the algorithm correct and effective. This algorithm displays its advantages of real-time and incremental, and it is proved to be correct and effective.
A single nucleotide polymorphism (SNP),as the most common form of genetic variation,has been widely studied to help analyze the possible association between diseases and *** gain more information,SNPs on a single chro...
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A single nucleotide polymorphism (SNP),as the most common form of genetic variation,has been widely studied to help analyze the possible association between diseases and *** gain more information,SNPs on a single chromosome are usually studied together,which constitute a *** haplotypes from biological experiments is usually very costly and time-consuming,which causes people to develop efficient methods to determine haplotypes from the computational *** problems and algorithms about haplotypes have been proposed to reduce the cost of studies of disease *** general,four categories of problems are widely researched:the haplotype assembly problem,the haplotype inference problem,the haplotype block partition problem,and the haplotype tagging SNP selection *** former two problems have been well reviewed by many researchers,whereas the latter two have not been comprehensively surveyed to our *** this paper,we try to make a detailed introduction to the four problems,especially the latter two.
Vertices, edges and triangle faces are the basic geometrical elements of triangle meshes. Iterative collapse or decimation of these elements is a significant approach to simplify the complex model. Research focuses on...
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Vertices, edges and triangle faces are the basic geometrical elements of triangle meshes. Iterative collapse or decimation of these elements is a significant approach to simplify the complex model. Research focuses on a method to define the quadrangle in the triangle mesh and puts forward a new mesh simplification algorithm based on quadrangle collapse. The algorithm utilizes iterative collapse of quadrangle to simplify models. In addition it maintains surface error approximations using quadric metrics. Three vertices and six faces are collapsed in every operation, so the algorithm rapidly generates high-quality approximations of polygonal models with minimal times of collapses than Garland's and Pan's algorithms. The experiment results demonstrate the efficiency of the new algorithm.
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