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Wuhan university Journal of Natural Sciences 2008年第4期13卷 417-420页

作者： FANG Wei XIAN Xuefeng ZHAO Pengpeng CUI Zhiming Jiangsu Provincial Key Laboratory of Computer InformationProcessing Technology Soochow University Suzhou 215006Jiangsu China

Fuzzy description logics are considered as the logical infrastructure of fuzzy knowledge representation on the semantic Web. To deal with fuzzy and dynamic knowledge on the semantic Web and its applications, a new fuzzy extension of Attribute Language with Complement based on dynamic fuzzy logic called the dynamic fuzzy description logic （DFALC） is presented. The syntax and semantics of DFALC are formally defined, and the forms of axioms and assertions are specified. The DFALC provides more reasonable logic foundation for the semantic Web, and overcomes the insufficiency of using fuzzy description logic FALC to act as logical foundation for the semantic Web. The extended DFALC is more expressive than the existing fuzzy description logics and present more fuzzy information on the semantic Web.

关键词： dynamic fuzzy logic description logic dynamic fuzzy description logic semantic Web

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Data expression method in enterprise application using J2EE architecture

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WSEAS Transactions on Communications 2008年第6期7卷 541-550页

作者： Zhang, Xiaoshuan Chen, Peijun Zhao, Ming College of Information and Electrical Engineering China Agricultural University Qinghua Donglu 17 Haidian Beijing 100083 China Jiangsu Provincial Key Laboratory of Computer Information Processing Technology Suzhou University Shixinjie 1 Suzhou Jiangsu 215006 China

With use of the Internet, web browser-enabled software applications are developed rapidly. Nowadays enterprises are paying more attention than ever on developing their business on the Web. The demand for rapidly delivering high quality web enabled software applications to the end users is high. The enterprise software developers are making efforts to develop the enterprise software applications that not only satisfy the business needs but also achieve the high quality within a short development process. However, the enterprise software development is normally complicated. For example, factors like the different enterprise environment, the critical business demand, the lack of knowledge and experience from the developers and so on can make the enterprise software development become rather hard work. Under such circumstances, something is needed to simplify the enterprise software development and also enable the sharing of the knowledge and experiences among the different developers. J2EE architecture is becoming the mainstream framework to develop the more complex enterprise application. The important problem arises, which is how to manage to each layer in J2EE and control the interior business data and the customer data, given that J2EE architecture has many complicated layers. There is respective data presentation in relevant layer of J2EE, with strictly rules to access and transform data objects between these layers. This paper adopts the case study method to discuss the data expression of J2EE and the detailed data expressing methods in corresponding layer with some instances. According to the Facade pattern of J2EE, it should control the access to data persistence layer seriously to protect important enterprise data and avoid showing database pattern to client directly. The data persistence layer hides behind the business logic layer and provide business interfaces via the business logic layer to communicate with the presentation layer to package the data persis

关键词： Enterprise software

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On automatic classification for agricultural products web pages in chinese based on LVQ network and ontology

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Journal of Computational information Systems 2008年第3期4卷 971-976页

作者： Wang, Chuanyi Fu, Zetian Zhang, Jian Hu, Liang Wang, Feng Zhang, Xiaoshuan China Agricultural University Beijing 100083 China Key Laboratory for Modern Precision Agriculture System Integration China Agricultural University Beijing 100083 China Beijing Information S and T University Beijing 100000 China Jiangsu Provincial Key Laboratory of Computer Information Processing Technology Suzhou University Suzhou 215000 China

The user often retrieves few anticipated results when searching information in Internet via generalized search engine due that the web pages also exist the synonymous and ambiguous characteristic. How to classify the webpage is the key point to construct vertical search engine, which is known as solution for the problems. This paper proposes a conceptual framework based on Learning Vector Quantization (LVQ) network and Ontology to automatic classification for the webpage from agricultural website. System test shows that the framework can automatically classify Chinese agricultural products web pages and perfectly resolve the synonymous problem.

关键词： Ontology

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Automated Essay Scoring Using the KNN Algorithm

Automated Essay Scoring Using the KNN Algorithm

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International Conference on computer Science and Software Engineering

作者： Li Bin Lu Jun Yao Jian-Min Zhu Qiao-Ming Provincial Key Laboratory of Computer Information Processing Technology Soochow University Suzhou China

ISBN: (纸本)9781424439027

The K-Nearest Neighbor (KNN) algorithm for text categorization is applied to CET4 essays. In this paper, each essay is represented by the vector space model (VSM). After removing the stop words, we chose the words, phrases and arguments as features of the essays, and the value of each vector is expressed by the term frequency and inversed document frequency (TF-IDF) weight. The TF and information fain (IG) methods are used to select features by predetermined thresholds. We calculated the similarity of essays with cosine in the KNN algorithm. Experiments on CET4 essays in the Chinese Learner English Corpus (CLEC) show accuracy above 76% is achieved.

关键词： Frequency Text categorization Writing Software algorithms Space technology Machine learning Performance gain computer science Software engineering Laboratories

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An Improved Algorithm of Decision Trees for Streaming Data Based on VFDT

An Improved Algorithm of Decision Trees for Streaming Data B...

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International Symposium on information Science and Engineering, ISISE

作者： Feixiong Li Quan Liu Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China

Decision tree is a good model of Classification. Recently, there has been much interest in mining streaming data. Because streaming data is large and no limited, it is unpractical that passing the entire data over more than one time. A one pass online algorithm is necessary. One of the most successful algorithms for mining data streams is VFDT(Very Fast Decision Tree).we extend the VFDT system to EVFDT(Efficient-VFDT) in two directions: (1)We present Uneven Interval Numerical Pruning (shortly UINP) approach for efficiently processing numerical attributes. (2)We use naive Bayes classifiers associated with the node to process the samples to detect the outlying samples and reduce the scale of the trees. From the experimental comparison, the two techniques significantly improve the efficiency and the accuracy of decision tree construction on streaming data.

关键词： Decision trees Classification tree analysis Data mining information science Laboratories information processing Buildings Classification algorithms H infinity control Histograms

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Directed diffusion algorithm based on cooperative mobile agent for wireless sensor networks

Directed diffusion algorithm based on cooperative mobile age...

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2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008

作者： Shu-Kui, Zhang Zhi-Ming, Cui Sheng-Rong, Gong Sun, Yong School of Computer Science and Technology Soochow University No1 Shizhi street Suzhou Jiangsu 215006 China Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University No1 Shizhi street Suzhou Jiangsu 215006 China

ISBN: (纸本)9781424421084

This paper proposed a directed diffusion algorithm based on cooperative mobile agent(MA), and considers MA in multihop environments and adopts directed diffusion to dispatch MA. The gradient in directed diffusion gives a hint to efficiently forward the MA among target sensors. MA accounts for performing data processing and making data aggregation decisions at nodes rather than bring data back to a central processor (sink).Using this algorithm, redundant sensory data will be eliminated. With appropriate parameters set, To demonstrate the feasibility of our algorithm , formal analysis and experimental results are presented, The results of our simulation show that MA based directed diffusion provides better performance than directed diffusion in terms of end-to-end delivery latency, packet delivery ratio, and energy consumption. © 2008 IEEE.

关键词： Mobile agents

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Adaptive Shadows Detection Algorithm Based on Gaussian Mixture Model

Adaptive Shadows Detection Algorithm Based on Gaussian Mixtu...

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International Symposium on information Science and Engineering, ISISE

作者： Yu-jiao XiaHou Sheng-rong Gong Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China Soochow University Suzhou Jiangsu CN

This paper proposed an adaptive shadows detection algorithm based on Gaussian Mixture Model to improve the performance of video object segmentation. This method takes advantage of luminance weight to model the background of the image and obtains a primary segmentation in CIE Luv color space. In this way, it improves the real-time ability of detection. It also becomes more efficient, comparing with the existing shadow detection algorithms which often need to set the threshold manually or get them through a training process. By using the Gaussian distribution, it is able to realize an adaptive shadow detection. At same time, the authors deal with the noise or the aim points uneven distribution by using horizontal filling and vertical filling. It improves the accuracy of segmentation. The experimental results have shown that this method achieves adaptive shadows detection and has strong robustness, high segmentation accuracy.

关键词： Detection algorithms Clustering algorithms Layout Gaussian distribution Pixel Object segmentation Filling Object detection Streaming media information science

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Ontology-Based Deep Web Synchronous-Annotation

Ontology-Based Deep Web Synchronous-Annotation

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ISECS International Colloquium on Computing, Communication, Control, and Management, CCCM

作者： PengYu Hu Wei Fang ZhiMing Cui Jiangsu Provincial Key Laboratory of Computer Information Processing Technology The Institute of Intelligent Information Processing and Application Soochow University Suzhou China

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.

关键词： Ontologies Databases Vocabulary Data mining Books Music Motion pictures

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Tree Kernel-Based Semantic Relation Extraction Using Unified Dynamic Relation Tree

Tree Kernel-Based Semantic Relation Extraction Using Unified...

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International Conference on Advanced Language processing and Web information technology (ALPIT)

作者： Longhua Qian Guodong Zhou Fang Kong Qiaomin Zhu Peide Qian Jiangsu Provincial Key Laboratory for Computer Information Processing Technology School of Computer Science and Technology Soochow University Suzhou China

This paper proposes a unified dynamic relation tree (DRT) span for tree kernel-based semantic relation extraction between entity names. The basic idea is to apply a variety of linguistics-driven rules to dynamically prune out noisy information from a syntactic parse tree and include necessary contextual information. In addition, different kinds of entity-related semantic information are unified into the syntactic parse tree. Evaluation on the ACE RDC 2004 corpus shows that the unified DRT span outperforms other widely-used tree spans, and our system achieves comparable performance with the state-of-the-art kernel-based ones. This indicates that our method can not only well model the structured syntactic information but also effectively capture entity-related semantic information.

关键词： Artificial neural networks Data mining Feature extraction Kernel Cities and towns Noise measurement Joining processes

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Exploring Various Features in Semantic Role Labeling

Exploring Various Features in Semantic Role Labeling

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International Conference on Advanced Language processing and Web information technology (ALPIT)

作者： Hongling Wang Guodong Zhou Qiaoming Zhu Peide Qian Jiangsu Provincial Key Lab for Computer Information Processing TechnologySchool of Computer Science and Technology Soochow University Suzhou China 215006

This paper explores the contributions of various features in semantic role labeling. Moreover, an optimal set of features is selected using a greedy strategy. Finally, an effective headword-driven pruning algorithm is proposed to filter out irrelavant instances. Evaluation on the CoNLL'2005 SRL benchmark corpus shows that our method achieved comparable performance with the best-reported ones on a single automatic parse tree.

关键词： Training Classification algorithms Accuracy Pediatrics Support vector machines Labeling System performance

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