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International Conference on Information Technology: New Generations (ITNG)

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

This paper tackles the problem of a user who is capable of reading or using documents written in a specific language, but who is not fluent enough in this specific language to use the right query terms to find the document. The design of Cross-Language Information Retrieval systems started since 1969 by Gerard Salton who enhanced his SMART system to retrieve documents in multiple languages, English and Spanish; however, the translation process is still considered to be a challenging problem. This paper is devoted to the evaluation of a Cross-Language search engine that uses Natural Language Processing techniques as a means of improving the search process of documents provided by two languages, English and Spanish. The research is implemented and evaluated on a real platform HyperManyMedia at Western Kentucky University. The implementation of the Cross-Language search engine follows a synergistic approach between (1) A Thesaurus-based Approach and (2) A Corpus-based Approach. In the case of the Thesaurus-based Approach, we use a simple bilingual listing of terms, phrases, concepts, and subconcepts where the hierarchical structure of the ontology is used to define the relationship between concepts/subconcepts. Also, we use a specific terminology that captures the domain of E-learning; those terms are associated with college name, course name, and lecture name which is presented in two languages. In the case of the Corpus-based Approach, we use the Term Vector Translation approach; the goal is to find statistical information about term usage between the two languages using techniques which map sets of term weights from English to Spanish and vice-versa.

关键词： Search engines Natural languages Information retrieval Natural language processing knowledge engineering Ontologies Speech processing knowledge representation Information technology Web mining

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Personalized Search Based on a User-Centered Recommender Engine

Personalized Search Based on a User-Centered Recommender Eng...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

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

Designing personalized search engines based on a recommender system that takes into consideration the user situated moment in relation to the subject matter and the context that governs user interest has been largely ignored. In this paper, we present a novel approach to integrating user interests into search within a recommender system that is guided by the semantic representation of the user and the content. In addition, our research tackles two problems of creating any recommender system: (a) the initial stage problem (how to provide recommendations to a user if the system hasn't been used yet) and (b) user context (providing the same user with different recommendations based on the context of their recent activity). Also the design of our recommender system is modular. It integrates and accommodates user's preferences by using User Relevance Feedback. Finally, we describe how the personalization aspects can increase the recommendation quality.

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Towards explanation-aware social software: Applying the mining and analysis continuum of explaining

Towards explanation-aware social software: Applying the mini...

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5th International Workshop on Explanation-Aware Computing, ExaCt 2010

作者： Atzmueller, Martin Roth-Berghofer, Thomas University of Kassel Knowledge and Data Engineering Group Wilhelmshöher Allee 73 34121 Kassel Germany GmbH Trippstadter Straße 122 67663 Kaiserslautern Germany Knowledge-Based Systems Group Department of Computer Science University of Kaiserslautern P.O. Box 3049 67653 Kaiserslautern Germany

Data mining methods build patterns or models. When presenting these, all or part of the result needs to be explained to the user in order to be understandable and for increasing the user acceptance of the patterns. In doing that, a variety of dimensions in the Mining and Analysis Continuum of Explaining (MACE) needs to be considered, e.g., from concrete to more abstract explanations. This paper discusses the application of the MACE in the context of social software. We consider applications of the proposed approaches in three social software systems, and show how the data mining results can seamlessly be analysed on the presented continuous dimensions and levels.

关键词： Application programs

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An adaptive multi-heuristic ant colony system for finding optimal elimination orderings in Bayesian networks

An adaptive multi-heuristic ant colony system for finding op...

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International Conference on Electrical engineering Computing science and Automatic Control

作者： Dong, Xuchu Zhang, Yonggang Cai, Dianbo Yu, Haihong Ye, Yuxin Department of Computer Science and Technology Jilin University China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education China Network Monitor Maintenance Centre of Jilin Branch China Telecom Corporation Limited Changchun Jilin China

ISBN: (纸本)9781424473120

To find an optimal elimination ordering for Bayesian networks, a multi-heuristic-based ant colony system named MHC-HS-ACS is proposed. MHC-HS-ACS uses a set of heuristics to guide the ants to search solutions. The heuristic set can evolve with the searching procedure in an adaptive way. MHC-HS-ACS also utilizes a heuristic-based local search to accelerate its convergence. Computational experiments show that MHC-HS-ACS can find very high quality solutions. © 2010 IEEE.

关键词： Bayesian networks

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MMIR: Mining multi-scale intervention rules in sub-complex system

MMIR: Mining multi-scale intervention rules in sub-complex s...

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12th International Asia Pacific Web Conference, APWeb 2010

作者： Jiaoling, Zheng Changjie, Tang Shaojie, Qiao Ning, Yang Yue, Wang Yu, Chen Jun, Zhu Institute of Database and Knowledge Engineering School of Computer Science Sichuan University Chengdu 610065 China Department of Software Engineering Chengdu University of Information Technology Chengdu 610225 China School of Information Science and Technology Southwest Jiaotong University Chengdu 610031 China National Centre for Birth Defects Monitoring Chengdu 610041 China

ISBN: (纸本)9780769540122

Intervention analysis is the common method to reveal relationships between objects in human as well as biological society. Data mining research community is just starting to pay attention to intervention analysis. As the traditional association rules are not successful at measuring intervention, this paper tries to mining intervention rules from time series data of subcomplex system. The main contributions of this study include: (1) introduces a new concept of intervention rules. It can quantitatively detect at what scale, how intensive and how long the intervention does make sense;(2) conduct wavelet transform on time series. The decomposition scale can denotes the intervention scale;(3) proposes a new concept named directional correlation to measure intervention intensity;(4) calculates the intervention intensity between time series data with different time delays. The time delay can uncover after how long the intervention takes place;(5) conducts experiments on real datasets. The results show that intervention rules do exist at different decomposition scale of the original data. Moreover, the number of rules discovered by multi-scale analysing methods is always 4 or 5 times more than those found by single scale methods. And the stability of rules discovered by the improved multi-scale mining algorithm MMIR is always 100%, while the stability of rules discovered by the basic multi-scale mining algorithm MMIR fluctuate around 70%. © 2010 IEEE.

关键词： Time series

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Semantically Enriched Recommender Engine: A Novel Collaborative Filtering Approach Using "User-to-User Fast Xor Bit Operation"

Semantically Enriched Recommender Engine: A Novel Collaborat...

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International Conference on Semantic Computing

作者： Leyla Zhuhadar Olfa Nasraoui Robert Wyatt Knowledge Discovery and Web Mining Laboratory Department of Computer Engineering and Computer Science University of Louisville Waterford KY USA Knowledge Discovery and Web Mining Laboratory Department of Computer Engineering and Computer Science University of Louisville Louisville KY USA Office of Distance Learning Western Kentucky University KY USA

In this paper, we focus on Collaborative Filtering to provide recommendations to users that fit their profiles. We employed two methods: (1) K-Nearest Neighbors classifier, and (2) a fast implementation of Collaborative Filtering approach: “user-to-user fast XOR bit operation”. Both techniques serve the same objective, which is modifying the user's ontology profile (semantic profile). Technically, Collaborative Filtering extends the user's ontology profile based on the interests of a community of similar users. Also, we describe the implementation of the recommender system on a real platform, known as Hyper Many Media at Western Kentucky University. Finally, we evaluate the system based on Top-n-Recall and Top-n-Precision. The results show an improvement in Recall and Precision using Collaborative Filtering.

关键词： Filtering Collaboration Semantics Search engines Data mining Educational institutions Boosting

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Trust Service Discovery by Opinions Classification on Virtual Communities

Trust Service Discovery by Opinions Classification on Virtua...

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International Conference on Networks Security, Wireless Communications and Trusted Computing, NSWCTC

作者： Qing Zhu Department of Computer Science Information School Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing China

ISBN: (纸本)9781424465972;9780769540115

Internet has become an excellent ecommerce platform for bringing together large numbers of buyers and sellers across wide geographic regions. Trust and reputation systems represent a. significant trend in decision support for Internet mediated service provision. However, most existing work assumes that all users have the same trust metrics, but in real life different users often have different preference of product attributes. This paper proposes trusted query navigation model by analyzing online customer reviews of trustworthiness of websites. The first step analyzes counting history feedback in the system offline and generates dynamic trust model by opinion classification. The second step presents trust evaluation ranking to help the user can easily discovery trust service of matching his needs. The experimental evaluation shows that the trusted query evaluation ranking has high trading efficiency, quick learning ability and satisfactory performance.

关键词： Business Feedback Portals History Web services computer security Data security Information security Wireless communication computer networks

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Local Methods for Estimating SimRank Score

Local Methods for Estimating SimRank Score

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International Asia-Pacific Web Conference (APWEB)

作者： Xu Jia Hongyan Liu Li Zou Jun He Xiaoyong Du Yuanzhe Cai Ministry of Education Key Laboratories of Data Engineering and Knowledge Engineering China Department of Computer Science Renmin University of China China Department of Management Science and Engineering Tsinghua University China Department of Computer Science University of Texas Arlington TX USA

SimRank is a well known algorithm which conducts link analysis to measure similarity between each pair of nodes (nodepair). But it suffers from high computational cost, limiting its usage in large-scale datasets. Moreover, Links between nodes are changing over time. It may be desirable to quickly approximate the similarity score between certain nodepair without performing a large-scale computation on the entire graph. In our approach we propose a method to efficiently estimate the similarity score using only a small subgraph of the entire graph. We call this novel algorithm “Local-SimRank”. The experimental results conducted on real datasets and synthetic dataset show that our algorithm efficiently produces good approximations to the global SimRank scores. Meanwhile, we prove that the Local-SimRank score LS(a, b) is always less than original SimRank score S(a, b) mathematically.

关键词： computer science Application software Web pages Data engineering knowledge engineering Algorithm design and analysis Large-scale systems computer science education Conference management knowledge management

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VANETs-Based Real-time Traffic Data Dissemination

VANETs-Based Real-time Traffic Data Dissemination

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2010 IEEE International Conference Conferenhce on Wireless Communications,Networking and Information Security(2010 IEEE 无线通信、网络技术与信息安全国际会议 WCNIS)

作者： Wenping Chen Department of Computer Science??Renmin University of China Beijing Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University of China) MOE

ISBN: (纸本)9781424458509

Traffic congestion is a very serious problem in large cities. With the number of vehicles increasing rapidly, especially in cities whose economy is booming, the situation is getting even worse. In this paper, by leveraging the techniques of Vehicular Ad hoc Networks (VANETs) we present a real-time abnormal traffic data dissemination protocol. Specifically, all vehicles running on the same road segment are regarded as a cluster to generate traffic message about this segment. To reduce communication cost, only abnormal traffic data is issued and spread to nearby road segments. By employing event-driven and period combined mechanism, the abnormal traffic messages are disseminated to the vehicles that probably need the messages in time. We propose a distance dependent forwarder selection method to disseminate traffic message. When transmitted inside a cluster, messages are forwarded along the segment from one end to the other based on the least hops principle;while transmitted among clusters, messages are transmitted in epidemic routing mode, which ensure the fast and reliable dissemination. To evaluate the performance of our protocol, we use the real traffic data of Beijing at peak hour. The simulation results demonstrate that our protocol is feasible and efficient for metropolitan-size city.

关键词： vehicular networks traffic real-time

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Using multi-agent system for business applications in multilingual ontologies

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Smart Innovation, Systems and Technologies 2010年 5卷 157-166页

作者： Håkansson, Anne Hartung, Ronald Jung, Jason J. Department of Computer and Systems Sciences Stockholm University Kista Sweden Department of Computer Science Franklin University Columbus OH United States Knowledge Engineering Laboratory Yeungnam University Gyeongsan Korea Republic of

ISBN: (纸本)9783642145933

In e-business, ontology technology is used for e-commerce and e-services. The ontologies are specifications of syntax and semantics of information, which provide a shared vocabulary to facilitate online services. For some requests, multiple ontologies are required to solve a problem, like for e-tourism. However, there are problems with using several ontologies. For example, finding and using the ontologies depends on the language used in the ontologies, and matching techniques. The matching includes word correspondence to the users' request and the equivalence between the ontologies. The matching is difficult due to differences between ontologies resulting from the lack of standards and development guidelines. This paper presents a multi-agent system wherein the agents use the users' request to search for multilingual ontologies. From the search results, the system facilitates communication between the users input and the ontologies to accomplish the request, which can be booking a train ticket or an event. Meta-agents keep track of the agents and manage the user-system communication. © Springer-Verlag Berlin Heidelberg 2010.

关键词： Multi agent systems

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