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Visual Ontology-Based Information Retrieval System

Visual Ontology-Based Information Retrieval System

引用

International Conference on Information Visualisation (IV)

作者： Leyla Zhuhadar Olfa Nasraoui Robert Wyatt Knowledge Discovery and Web Mining Lab Department of Computer Engineering and Computer Science University of Louisville KY USA

The semantic Web has been evolved as a key technology, bringing new insights and solutions to well documented problems in e-learning. The research field of semantic e-learning covers a wide range of research problems. In this paper, we present an approach to visualize an ontology driven information retrieval system in the context of E-learning. This approach has been implemented on the HyperManyMedia platform, and is already being used by online students at WKU. The design of this work is based on the following steps: (1) presenting the HyperManyMedia domain as a tree consisting of concepts and subconcepts where the leaves are the documents (lectures), (2) embedding Nutch search engine into the platform, (3) reconfiguring Nutch search engine to accommodate the semantic search, (4) using Prefuse as a visual tool to present the ontology as a graph, and (5) embedding the graph into the platform as an applet so that learners can navigate visually through the ontology of the domain by clicking on nodes.

关键词： Ontologies Information retrieval Electronic learning Semantic Web Search engines Visualization Navigation knowledge engineering Taxonomy Educational institutions

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An extended multi-layered blackboard approach for the optimization of world-spanning query execution plans

An extended multi-layered blackboard approach for the optimi...

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International Conference for Internet Technology and Secured Transactions (ICITST)

作者： Peter Paul Beran Erich Schikuta Faculty of Computer Science Department of Knowledge and Business Engineering University of Technology Vienna Vienna Austria

New application domains ranging from the area of computational science (e.g. CERN Datagrid) to international business processes (e.g. Wal-Mart logistics) demand ever increasing storage capacities on a global scale. Therefore the ability to query and access data efficiently is one of the major challenges that drive research and development in the area of wide distributed data management. Due to the situation of a huge variety of underlying heterogeneous and homogenous infrastructures, where each showing specific hard- and software resources and a number of possible data sources, the optimization of the access process to the desired data is a challenging task. Hence, this paper introduces a novel heuristic approach for the optimization of query execution plans (QEP) on a global scale based on an extended multi-layered blackboard mechanism to determine which available (1) data, (2) resources, and (3) operations to use. The proposed method is illustrated by an application scenario of finding an optimal QEP for the retrieval of music information from an online music store.

关键词： Distributed databases Parallel processing Database systems Peer to peer computing Acceleration computer science knowledge engineering Application software Logistics Drives

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Incremental computation for MEDIAN cubes in what-if analysis

Incremental computation for MEDIAN cubes in what-if analysis

引用

Joint International Conference on Advances in Data and Web Management, APWeb/WAIM 2009

作者： Xiao, Yanqin Zhang, Yansong Wang, Shan Chen, Hong Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Computer Center Hebei University Baoding Hebei 071002 China Department of Computer Science Harbin Finance College Harbin 150030 China

ISBN: (纸本)9783642006715

What-if analysis is an important type of DSS analysis processing procedure. It analyzes hypothetical scenarios based on historical data. The data cube view must be updated when the what-if condition is changed. Since source data must be kept in order to compute the new aggregate value when new tuples are inserted or deleted, in what-if analysis, incrementally computing a data cube for holistic aggregation functions is a difficult problem. In this paper, we adopt delta cube strategy and work area technique to incrementally compute data cube for MEDIAN function. The size of work area has important influence on the efficiency of the incremental computing. This paper optimizes the size of work area based on the number and the cardinality of dimension attributes of the cuboid. Performance study shows that our algorithms are effective over large databases. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Geometry

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Efficient incremental computation of CUBE in multiple versions what-if analysis

Efficient incremental computation of CUBE in multiple versio...

引用

Joint International Conference on Advances in Data and Web Management, APWeb/WAIM 2009

ISBN: (纸本)9783642006715

What-if analysis is an important method to analyze the hypothetical scenarios based on the historical data. It provides useful information for the decision- maker. Multiple versions are critical to what-if analysis. In this paper, we analyze the problem of multiple versions data processing and the incremental computation of cubes in what-if analysis, proposing a strategy to process multiple versions of what-if data. Our solution can adopt different data processing methods according to the type of aggregate functions, the efficiency of multiple versions data processing is improved. Furthermore, we proposes an algorithm of incremental computation of CUBE for max(min) function to reduce the access time of fact table, and the experimental results showed that the performance is improved about 10%. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Decision making

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Fuzzy multiresolution neural networks

Fuzzy multiresolution neural networks

引用

International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009

作者： Ying, Li Qigang, Shang Na, Lei Symbol Computation and Knowledge Engineer Lab. of Ministry of Education College of Computer Science and Technology China Department of Mechanical and Engineering Academy of Armored Force Engineering Beijing China Department of Mechanical and Engineering Academy of Armored Force Technology Changchun China College of Mathematics China Jilin University Changchun 130021 China

ISBN: (纸本)3642052525

A fuzzy multi-resolution neural network (FMRANN) based on particle swarm algorithm is proposed to approximate arbitrary nonlinear function. The active function of the FMRANN consists of not only the wavelet functions, but also the scaling functions, whose translation parameters and dilation parameters are adjustable. A set of fuzzy rules are involved in the FMRANN. Each rule either corresponding to a subset consists of scaling functions, or corresponding to a sub-wavelet neural network consists of wavelets with same dilation parameters. Incorporating the time-frequency localization and multi-resolution properties of wavelets with the ability of self-learning of fuzzy neural network, the approximation ability of FMRANN can be remarkable improved. A particle swarm algorithm is adopted to learn the translation and dilation parameters of the wavelets and adjusting the shape of membership functions. Simulation examples are presented to validate the effectiveness of FMRANN. © 2009 Springer-Verlag.

关键词： Fuzzy neural networks

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Extracting attributes from deep web interface using instances

Extracting attributes from deep web interface using instance...

引用

2009 WRI World Congress on computer science and Information engineering, CSIE 2009

作者： Hao, Liang Fei, Ren Wanli, Zuo Fengling, He Junhua, Wang College of Computer Science and Technology Jilin University Changchun 130012 China Department of Information Changchun Taxation College Changchun 130117 China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China

ISBN: (纸本)9780769535074

There is myriad high quality information in the Deep Web and the feasible method to access the Deep Web is through the query interface of the Deep Web. It's necessary to extract abundant attributes and semantic relation description from the query interface. Automatic extracting attributes from the query interface and automatically translating a query is a solvable way for addressing the current limitations in accessing Deep Web data sources. We design a framework to automatically extract the attributes and instances from the query interface using the WordNet as a kind of ontology technique to enrich the semantic description of the attributes. Each attribute is extended into a candidate attribute set in the form of a hierarchy tree. At the same time, the hierarchy tree generated by ontology describes the semantic relation of the attributes in the same query interface. We carry out our experiments in the real-world domain. The results of the experiments showed the validation of query translation framework. © 2008 IEEE.

关键词： Ontology

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The tradeoff of delta table merging and re-writing algorithms in what-if analysis application

The tradeoff of delta table merging and re-writing algorithm...

引用

Joint International Conference on Advances in Data and Web Management, APWeb/WAIM 2009

作者： Zhang, Yansong Zhang, Yu Xiao, Yanqin Wang, Shan Chen, Hong Key Laboratory of the Ministry of Education for Data Engineering and Knowledge Engineering Renmin University of China Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Department of Computer Science Harbin Finance College Harbin 150030 China Computer Center Hebei University Baoding Hebei 071002 China

ISBN: (纸本)9783642006715

What-if analysis can provide more meaningful information than classical OLAP. Multi-scenario hypothesis based on historical data needs efficient what-if data view support. In general, delta table for what-if analysis is more general than other solutions such as query re-writing prototype of Sesame. Delta table is independent of base table and is more suitable to represent complex hypothetical updates and multi-version hypothetical updates. Due to low efficiency of traditional delta table merging algorithm which is based on set operation, there are few researches focus on delta table merging algorithm but on query re-writing algorithm. By analyzing the difference between what-if query and what-if analysis and improving the delta table merging algorithm, we propose novel algorithms without set operation of difference. Considering the feature of aggregate operations in OLAP analysis, pre-merge algorithm is presented without the generation of what if data view before group-bys in the scenario of SUM, AVERAGE and COUNT function OLAP queries. In our experiments, the pre-merge algorithm greatly improved the efficiency of delta table merging procedure which is close to base group-by statement and superior to the re-writing algorithm. A complete comparison between all candidate delta table merging algorithms and re-writing algorithm with different what-if update conditions of update, deletion, insertion and mixed what-if updates is exhibited in our experiments, the policy of what-if analysis among different types is also discussed. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Merging

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Adaptive Tourism Modeling and Socialization System

Adaptive Tourism Modeling and Socialization System

引用

IEEE International Conference on Computational science and engineering, CSE

作者： Bruno Coelho Constantino Martins Ana Almeida GECAD-Knowledge Engineering and Decision Support Group Computer Science Department Institute of Engineering Polytechnic of Porto Porto Portugal

This paper presents an undertaken research work about the development of an Adaptive Tourism Modeling System which attempts to correctly model a tourism Web application user profile. This paper will follow the methodology used behind the concept of the application, `User Modeling as a process', which consists of three specific modules in order to achieve a clear user modeling technology. The user representation module devises a collection of knowledge representation formalisms that co-exist in order to constitute the system's view of the user; the user reasoning module is responsible for the execution of several inference tasks as well as the generation of possibly new and valuable information about the user, using the latter module. The user concept that comes out of these two modules will ultimately be used by various kinds of application-level systems, namely a recommender system, therefore instantiating a project-dependent third module.

关键词： knowledge engineering Recommender systems Artificial intelligence computer science Adaptive systems Application software knowledge representation Adaptation model Monitoring Decision support systems

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Efficient Algorithm for Computing Link-Based Similarity in Real World Networks

Efficient Algorithm for Computing Link-Based Similarity in R...

引用

IEEE International Conference on Data Mining (ICDM)

作者： Yuanzhe Cai Gao Cong Xu Jia Hongyan Liu Jun He Jiaheng Lu Xiaoyong Du Key Laboratories of Data Engineering and Knowledge Engineering Ministry of Education China Department of Computer Science Renmin University of China China Department of Computer Science University of Aalborg Denmark Department of Management Science and Engineering Tsinghua University China

Similarity calculation has many applications, such as information retrieval, and collaborative filtering, among many others. It has been shown that link-based similarity measure, such as SimRank, is very effective in characterizing the object similarities in networks, such as the Web, by exploiting the object-to-object relationship. Unfortunately, it is prohibitively expensive to compute the link-based similarity in a relatively large graph. In this paper, based on the observation that link-based similarity scores of real world graphs follow the power-law distribution, we propose a new approximate algorithm, namely Power-SimRank, with guaranteed error bound to efficiently compute link-based similarity measure. We also prove the convergence of the proposed algorithm. Extensive experiments conducted on real world datasets and synthetic datasets show that the proposed algorithm outperforms SimRank by four-five times in terms of efficiency while the error generated by the approximation is small.

关键词： computer networks Collaboration Data engineering knowledge engineering computer science Iterative algorithms Filtering Data mining Helium computer science education

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Learning Discriminative Multi-scale and Multi-position LBP Features for Face Detection Based on Ada-LDA

Learning Discriminative Multi-scale and Multi-position LBP F...

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2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

作者： Kwang Ho An Myung Jin Chung So Hee Park Ki Young Moon Yun Su Chung Electrical Engineering and Computer Science Department Korea Advanced Institute of Science and Techn Knowledge-based Information Security & Safety Research Department Electronics and Telecommunications

ISBN: (纸本)9781424447749

This paper presents a novel approach for face detection, which is based on the discriminative MspLBP features selected by a boosting technique called the Ada-LDA method. By scanning the face image with a scalable sub-window, many sub-regions are obtained from which the MspLBP features are extracted to describe the local structures of a face image. From a large pool of the MspLBP features within the face image, the most discriminative MspLBP features that are trained by two alternative LDA methods depending on the singularity of the within-class scatter matrix of the training samples are selected under the framework of AdaBoost. To verify the feasibility of our face detector, we performed extensive experiments on the MIT-CBCL and MIT+CMU face test sets. Given the same number of features, the proposed face detector shows a detection rate of 25％ higher than the well-known Viola's detector at a given false positive rate of 10％. Challenging experimental results prove that our face detector can show promising detection performance with only a small number of the discriminative MspLBP features. It can also provide real-time performance. Our face detector can operate at over 16 frames per second.

关键词： Facial Recognition Face Face detector detection rate (DR) S-matrix theory LBP gene LBP multi-scale numerical invariant

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