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Using probabilistic latent semantic analysis for personalized web search

Using probabilistic latent semantic analysis for personalize...

引用

7th Asia-Pacific Web Conference on Web Technologies Research and Development - APWeb 2005

作者： Lin, Chenxi Xue, Gui-Rong Zeng, Hua-Jun Yu, Yong Apex Data and Knowledge Management Lab. Department of Computer Science and Engineering Shanghai JiaoTong University Shanghai 200030 China Microsoft Research Asia 49 Zhichun Road Beijing 100080 China

Web users use search engine to find useful information on the Internet. However current web search engines return answer to a query independent of specific user information need. Since web users with similar web behaviors tend to acquire similar information when they submit a same query, these unseen factors can be used to improve search result. In this paper we present an approach that mines these unseen factors from web logs to personalized web search. Our approach is based on probabilistic latent semantic analysis, a model based technique that is used to analyze co-occurrence data. Experimental results on real data collected by MSN search engine show the improvements over traditional web search. © Springer-Verlag Berlin Heidelberg 2005.

关键词： World Wide Web

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Document clustering in antimicrobial peptides research

Document clustering in antimicrobial peptides research

引用

11th Americas Conference on Information Systems, AMCIS 2005

作者： Peng, Yi Yan, Nian Kou, Gang Chen, Zhengxin Shi, Yong Peter Kiewit Institute of Information Science Technology and Engineering University of Nebraska Omaha NE 68182 United States Chinese Academy of Sciences Research Center Data Technology and Knowledge Economy Beijing 100039 China

ISBN: (纸本)9781604235531

Antimicrobial peptides are small peptides encoded by genes. The research area of antimicrobial peptides has attracted intense attention in recent years because "their potential use in the cure of infectious diseases caused by pathogens that have become counteractive to traditional antibiotics" (Boman 1994). There exist huge amount of antimicrobial peptides research articles and this number is continuously increasing. Although some biomedical databases, such as PubMed, have been well established, they provide only query-based information retrieval and end-users need to manually find out relevant information from thousands of retrieved articles. The objective of this paper is to apply one of the text mining techniques, document clustering, which groups similar documents into clusters, to text documents collected from PubMed using keyword "antimicrobial peptides". The results of our work can help researchers to discover meaningful groups of antimicrobial peptides articles in an efficient manner.

关键词： Information retrieval

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Using optimization-based classification method for massive datasets

Using optimization-based classification method for massive d...

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11th Americas Conference on Information Systems, AMCIS 2005

作者： Peng, Yi Shi, Yong Kou, Gang Chen, Zhengxin Peter Kiewit Institute of Information Science Technology and Engineering University of Nebraska Omaha NE 68182 United States Chinese Academy of Sciences Research Center on Data Mining and Knowledge Management Beijing 100039 China

ISBN: (纸本)9781604235531

Optimization-based algorithms, such as Multi-Criteria Linear programming (MCLP), have shown their effectiveness in classification. Nevertheless, due to the limitation of computation power and memory, it is difficult to apply MCLP, or similar optimization methods, to huge datasets. As the size of today's databases is continuously increasing, it is highly important that data mining algorithms are able to perform their functions regardless of dataset sizes. The objectives of this paper are: (1) to propose a new stratified random sampling and majority-vote ensemble approach, and (2) to compare this approach with the plain MCLP approach (which uses only part of the training set), and See5 (which is a decision-tree-based classification tool designed to analyze substantial datasets), on KDD99 and KDD2004 datasets. The results indicate that this new approach not only has the potential to handle arbitrary-size of datasets, but also outperforms the plain MCLP approach and achieves comparable classification accuracy to See5.

关键词： Classification (of information)

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Multiple principal component analyses and projective clustering

Multiple principal component analyses and projective cluster...

引用

International Workshop on database and Expert Systems Applications

作者： N. Kerdprasop K. Kerdprasop Data Engineering and Knowledge Discovery Research Unit School of Computer Engineering Suranaree University슠of Technology Thailand

Projective clustering is a clustering technique for high dimensional data with the inherent sparsity of the data points. To overcome the unreliable measure of similarity among data points in high dimensions, all data points are projected to a lower dimensional sub-space. Principal component analysis (PCA) is an efficient method to dimensionality reduction by projecting all points to a lower dimensional subspace so that the information loss is minimized. However, PCA does not handle well the situation that different clusters are formed in different subspaces. We propose a method of multiple principal component analysis for iteratively computing projective clusters. The objective function is designed to determine the subspace associated with each cluster. Some experiments have been carried out to show the effectiveness of the proposed method.

关键词： Principal component analysis Clustering algorithms data engineering Partitioning algorithms knowledge engineering Algorithm design and analysis Statistical analysis Clustering methods Conferences Spatial databases

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A multi-agent framework for a P2P data sharing facility

A multi-agent framework for a P2P data sharing facility

引用

International Conference on Advanced Information Networking and Applications (AINA)

作者： S.M. Deen Department of Computer Science Data and Knowledge Engineering (DAKE) Group University of Keele Staffordshire UK

The paper presents a general architecture for a P2P data sharing facility within a multi-agent framework, where peers as autonomous high-level nodal agents cooperate with each other to solve global tasks. A node may have several lower level local agents including local databases and partial global ontologies. In addition there are also minder agents coordinating the activities of the peers that offer the same type of service, thus providing fault-tolerance. The ability of this architecture in data and task sharing has been demonstrated by considering query processing and directory update strategies.

关键词： Peer to peer computing Fault tolerance Query processing Spread spectrum communication Transaction databases knowledge engineering Computer science Computer architecture Ontologies Internet

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Density-biased clustering based on reservoir sampling

Density-biased clustering based on reservoir sampling

引用

International Workshop on database and Expert Systems Applications

作者： K. Kerdprasop N. Kerdprasop P. Sattayatham Data Engineering and Knowledge Discovery (DEKD) Research Unit School of Computer Engineering Suranaree University슠of Technology Thailand

Clustering is a task of grouping data based on similarity. A popular k-means algorithm groups data by firstly assigning all data points to the closest clusters, then determining the cluster means. The algorithm repeats these two steps until it has converged. We propose a variation called weighted k-means to improve the clustering scalability. To speed up the clustering process, we develop the reservoir-biased sampling as an efficient data reduction technique since it performs a single scan over a data set. Our algorithm has been designed to group data of mixture models. We present an experimental evaluation of the proposed method.

关键词： Reservoirs Sampling methods Clustering algorithms Iterative algorithms Partitioning algorithms data engineering databases knowledge engineering Councils Scalability

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Prediction of Wastewater Pre-Precipitation Variables Using Self-Organizing Networks

Prediction of Wastewater Pre-Precipitation Variables Using S...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： P. Isaias S. Nilsson A. Stathaki R.E. King Data and Knowledge Engineering Group Computer Research Institute Athens Athens Greece Environmental Research Institute IVL Stockholm Sweden Electrical Engineering and Computer Science University of Patras Greece

This paper describes the derivation and design of an array of self-organizing networks trained by inductive learning for one step ahead prediction of the outputs of the pre-precipitation stage of a wastewater treatmen... 详细信息

关键词： Self-organizing networks Wastewater treatment Mathematical model Neural networks Effluents Predictive models Predictive control Machine learning Chemicals Instruments

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SemCrypt - Ensuring Privacy of Electronic Documents Through Semantic-Based Encrypted Query Processing

SemCrypt - Ensuring Privacy of Electronic Documents Through ...

引用

International Conference on data engineering Workshops

作者： M. Schrefl K. Grun J. Dorn Department of Business Informatics-Data & Knowledge Engineering Johannes Kepler University Linz Linz Austria EC3-Electronic Commerce Competence Center Vienna Austria

The trend towards outsourcing increases the number of documents stored at external service providers. This storage model, however, raises privacy and security concerns because the service providers cannot be trusted with respect to maintaining the privacy of the documents. The research project SemCrypt^1 explores techniques for processing queries and updates over encrypted XML documents stored at untrusted servers. By performing encryption and decryption only on the client and not on the server, SemCrypt guarantees that neither the document structure nor the document content are disclosed on the server. Filtering query results and processing as much as possible of the query/update statement on the server does not depend on special encryption techniques. Instead, the chosen approach exploits the structural semantics of XML documents and uses standard, well-proven encryption techniques. SemCrypt thus enables to query and update encrypted XML documents on untrusted servers while ensuring data privacy.

关键词： Cryptography Query processing XML data privacy Semantic Web Outsourcing Secure storage Web server Web and internet services Relational databases

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A testbed for evaluating human interaction with ubiquitous computing environments

A testbed for evaluating human interaction with ubiquitous c...

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International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities (TRIDENTCOM)

作者： E. O'Neill M. Klepal D. Lewis T. O'Donnell D. O'Sullivan D. Pesch Dept. of Comput. Sci. Trinity Coll. Dublin Ireland Centre for Adaptive Wireless System Cork Institute of Technology Ireland Knowledge and Data Engineering Group Trinity College Dublin Ireland

Core to ubiquitous computing environments are adaptive software systems that adapt their behavior to the context in which the user is attempting the task the system aims to support. This context is strongly linked with the physical environment in which the task is being performed. The efficacy of such adaptive systems is thus highly dependent on the human perception of the provided system behavior within the context represented by that particular physical environment and social situation. However, effective evaluation of human interaction with adaptive ubiquitous computing technologies has been hindered by the cost and logistics of accurately controlling such environmental context. This paper describes TATUS, a ubiquitous computing simulator aimed at overcoming these cost and logistical issues. Based on a 3D games engine, the simulator has been designed to maximize usability and flexibility in the experimentation of adaptive ubiquitous computing systems. We also describe how this simulator is interfaced with a testbed for wireless communication domain simulation.

关键词： Testing Humans Ubiquitous computing Computational modeling Adaptive systems Costs Software systems Programmable control Adaptive control Logistics

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Evaluation of APeLS - An adaptive elearning service based on the multi-model, metadata-driven approach

引用

3rd International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH 2004

作者： Conlan, Owen Wade, Vincent P. Knowledge and Data Engineering Group Trinity College Dublin Ireland

ISBN: (纸本)3540228950

The evaluation of learner and tutor feedback is essential in the production of high quality personalized eLearning services. There are few evaluations available in the Adaptive Hypermedia domain relative to the amount of research interest this domain is attracting. Many of the papers in this domain focus on the technological design of systems without justifying the designs through the lessons learned from evaluations. This paper evaluates the usability and effectiveness of using the multi-model, metadata-driven approach for producing rich adaptive eLearning solutions that remain content and domain independent. Through this independence, the eLearning services developed can utilize many pedagogical approaches and a variety of models to produce a wide range of highly flexible solutions. This paper identifies benefits to learners brought through adopting the multi-model approach gathered over four years of student evaluation. It briefly describes the evaluation of the Adaptive Personalized eLearning Service (APeLS), a personalized eLearning service based on a generic adaptive engine. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Quality control

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