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Proximity-based rocchio's model for pseudo relevance 12

Proximity-based rocchio's model for pseudo relevance

引用

35th Annual ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2012

作者： Miao, Jun Huang, Jimmy Xiangji Ye, Zheng Information Retrieval and Knowledge Management Research Lab. Department of Computer Science and Engineering York University Toronto ON Canada Information Retrieval and Knowledge Management Research Lab. School of Information Technology York University Toronto ON Canada

ISBN: (纸本)9781450316583

Rocchio's relevance feedback model is a classic query expansion method and it has been shown to be effective in boosting information retrieval performance. The selection of expansion terms in this method, however, does not take into account the relationship between the candidate terms and the query terms (e.g., term proximity). Intuitively, the proximity between candidate expansion terms and query terms can be exploited in the process of query expansion, since terms closer to query terms are more likely to be related to the query topic. In this paper, we study how to incorporate proximity information into the Rocchio's model, and propose a proximity-based Rocchio's model, called PRoc, with three variants. In our PRoc models, a new concept (proximity-based term frequency, ptf) is introduced to model the proximity information in the pseudo relevant documents, which is then used in three kinds of proximity measures. Experimental results on TREC collections show that our proposed PRoc models are effective and generally superior to the state-of-the-art relevance feedback models with optimal parameters.A direct comparison with positional relevance model (PRM) on the GOV2 collection also indicates our proposed model is at least competitive to the most recent progress. © 2012 ACM.

关键词： knowledge management

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York University at TREC 2012: CrowdSourcing Track 21

York University at TREC 2012: CrowdSourcing Track

引用

21st Text REtrieval Conference, TREC 2012

作者： Hu, Qinmin Xu, Zhi Huang, Xiangji Ye, Zheng Information Retrieval and Knowledge Managment Lab York University Toronto Canada Department of Computer Science & Engineering York University Toronto Canada School of Information Technology York University Toronto Canada

The objective of this work is to address the challenges in managing and analyzing crowdsourcing in the information retrieval field. In particular, we would like to answer the following questions: (1) how to control the quality of the workers when crowdsourcing? (2) How to design the interface such that the workers are willing to participate in and are driven to give useful feedback information? (3) How to make use the crowdsourcing information in the IR systems? The crowdsourcing system called CrowdFlower is employed and four classic information retrieval models are applied in our proposed approaches. Our experimental results show that the IR systems refine the results crowdsourcing by minimizing the manual work and the cost is much less. © 2012 21st Text REtrieval Conference, TREC 2012. All rights reserved.

关键词： Crowdsourcing

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Design and Realization of Competence Profiling Tool for Effective Selection of Professionals in Maintenance Management

Design and Realization of Competence Profiling Tool for Effe...

引用

IEEE International Conference on Systems, Man, and Cybernetics

作者： Mahdi Bohlouli Fazel Ansari Madjid Fathi Institute of Knowledge Based Systems and Knowledge Management (KBS & KM) Department of Electrical Engineering and Computer Science University of Siegen

ISBN: (纸本)9781467317139

Enterprises and industrial companies strive to improve their functional performance by identification of core competencies in order to utilize human resources and optimise the knowledge integration processes of the company. In addition, maintenance operations are one of the most important sections in industrial companies which consist of key personnel and also explicit and implicit knowledge resources that have direct effects on product quality and return on investment. In the context of implicit knowledge resources, the principal objective is firstly to identify knowledge holders who are mainly domain experts (e.g. Chief Maintenance Officer-CMO) and maintenance practitioners (e.g. engineers, technicians, etc.), and secondly to measure their domain expertise. This paper presents the concept and implementation results of an interdisciplinary research which aims at improving the knowledge measuring of maintenance practitioners. In this way, the companies are enabled to deduce rate of human failures in maintenance operations by allocating the right professionals in the right positions using competency profiling of employees. The implementation results in developing a competence profiling tool as an add-on for computerized Maintenance Management Information Systems (CMMIS), which is previously developed in the Institute of knowledge Based Systems and knowledge Management (KBS & KM).

关键词： Competency Profiling knowledge Measuring Maintenance Management Human Resource Management CMMIS MAINTENANCE MANAGEMENT Professional Companies competence knowledge based systems Industrial enterprises Epistemology functional performance Interdisciplinary Studies Outcomes of Education Human Resource Management

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A novel based-node level security strategy in wireless sensor network

A novel based-node level security strategy in wireless senso...

引用

2012 International Conference on Information Management, Innovation Management and Industrial engineering, ICIII 2012

作者： Zheng, Yue-Feng Chen, Zhuo-Ran Han, Jia-Yu Li, Zheng BoDa College Jilin Normal University Si Ping China College of Computer Science and Technology Jilin University Key Laboratory of SymComputation and Knowledge Engineering Chang Chun China Computer Department BoDa College Jilin Normal University Si Ping China

ISBN: (纸本)9781467319324

In Wireless Sensor Networks,Security is very important, especially in the networks which require high security. This paper raises a method to establish key distribution scheme, based on node layer security system, which combines with the group key distribution and identification of encryption. This method can make the two nodes carry on communication in a secure environment when identified, at the same time, communication in the safe environment between groups can also be guaranteed. The results show that the ability of resistance to attack, Sybil attack, node increases the attack, the node replication attacks can effectively be stopped. At the same time, further illustrates that the adoption of this security strategy for wireless sensor network security enhancement. Simulation results show that, the structure of security system we proposed is safe and feasible. © 2012 IEEE.

关键词： Network security

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Clustering Heterogeneous Data Sets

Clustering Heterogeneous Data Sets

引用

Proceedings of the Latin American Web Congress (LA-Web)

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

Recent years have seen an increasing interest in clustering data comprising multiple domains or modalities, such as categorical, numerical and transactional, etc. This kind of data is sometimes found within the context of clustering multiview, heterogeneous, or multimodal data. Traditionally, different types of attributes or domains have been handled by first combining them into one format (possibly using some type of conversion) and then following with a traditional clustering algorithm, or computing a combined distance matrix that takes into account the distance values for each domain, then following with a relational or graph clustering approach. In other cases where data consists of multiple views, multiview clustering has been used to cluster the data. In this paper, we review the existing approaches such as multiview clustering and discuss several additional approaches that can be harnessed for the purpose of clustering heterogeneous data once they are adapted for this purpose. The additional approaches include ensemble clustering, collaborative clustering and semi-supervised clustering.

关键词： Clustering algorithms Collaboration Peer to peer computing Partitioning algorithms Hidden Markov models Linear programming Distortion measurement

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Research of the timer granularity based on linux

Research of the timer granularity based on linux

引用

International Conference on computer, Informatics, Cybernetics and Applications 2011, CICA 2011

作者： Qingtian, Geng Nan, Jiang Hongwei, Zhao Junling, Liu Department of Computer Science and Technology Jilin University Changchun 130012 China Changchun Normal University Changchun 130032 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9789400718388

Time interrupts play an important role in the system. When time interrupts occur, system will inspect process running state, providing an opportunity to schedule, which is important for improving system real time performance. For the low system real-time ability of Linux, the paper adopt enhancing time granularity to improve system real time ability by means of one-shot triggering mode. The kernel of one-shot mode time interrupt is that: the system need not have to respond to any change every time, but only make response when having to respond. Experimental results show that the system real-time ability of Linux is improved through enhancing time granularity. © 2012 Springer science+Business Media B.V.

关键词： Linux

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Efficient approximation of the maximal preference scores by lightweight cubic views

Efficient approximation of the maximal preference scores by ...

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15th International Conference on Extending Database Technology, EDBT 2012

作者： Chen, Yueguo Cui, Bin Du, Xiaoyong Tung, Anthony K. H. Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE China Department of Computer Science Peking University Beijing China School of Information Renmin University of China Beijing China School of Computing National University of Singapore Singapore Singapore

ISBN: (纸本)9781450307901

Given a multi-features data set, a best preference query (BPQ) computes the maximal preference score (MPS) that the tuples in the data set can achieve with respect to a preference function. BPQs are very useful in applications where users want to efficiently check whether many individual data sets contain tuples that are of interest to them. Although a BPQ can be naïvely answered by issuing a top-1 query and computing the score from the returned tuple, doing so might require to load a larger number of tuples externally. In this paper, we address the problem of efficient processing BPQs by using lightweight cubic (3-dimensional) views. With these in-memory views, the MPSs of BPQs can be efficiently estimated with an error bound guaranteed, by paying only a small number of I/Os. Extensive experimental results over real-life data sets show that our approximate solution can achieve the efficiency of up to three orders of magnitude compared to exact solutions, with certain accuracy guaranteed. © 2012 ACM.

关键词： best preference score materialized views preference query top-k query

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Evaluation of knowledge sharing in a collaborative software

Evaluation of knowledge sharing in a collaborative software

引用

5th International Multi-Conference on engineering and Technological Innovation, IMETI 2012

作者： Juliani, Douglas Juliani, Jordan De Abreu, Aline França De Souza, João Artur Postgraduate Programme in Engineering and Knowledge Management Federal University of Santa Catarina - UFSC Brazil Department of Computer Science Federal Institute of Santa Catarina - IFSC Brazil Department of Library and Information Management State University of Santa Catarina - UDESC Florianopolis Brazil

ISBN: (纸本)9781936338740

The widespread use of collaborative applications as a means of communication, research and collation of information, among others, has significantly accelerated the acquisition, dissemination, and especially the sharing of information and knowledge among individuals. Thus, understanding the factors influencing this process is crucial to the success of a software based on the contribution of people. In this research, among the various factors analyzed, it was found that the usability and the characteristics of individuals are crucial to assess knowledge sharing in a knowledge-based system, in this case, the social software PreipoPublico. We chose to use questionnaire with 23 items as an evaluation tool that, based on two existing, refurbished and was validated by pre-testing and statistical technique. Being 19 closed questions (categorical measures) and 4 open, descriptive. Results showed that users are predisposed to share their knowledge and information about product prices in the software. Still, it was shown that the system has a high degree of usability, despite some difficulties encountered by most respondents coming from the fact it is the first system to access them. The comments collected from the open questions suggest system improvements. Copyright © 2008 by the International Institute of Informatics and Systemics.

关键词： knowledge based systems

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An extensive experimental comparison of methods for multi-label learning

An extensive experimental comparison of methods for multi-la...

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作者： Madjarov, Gjorgji Kocev, Dragi Gjorgjevikj, Dejan Džeroski, Sašo Faculty of Computer Science and Engineering Ss. Cyril and Methodius University Rugjer Boshkovikj 16 1000 Skopje Macedonia Department of Knowledge Technologies Jožef Stefan Institute Jamova cesta 39 1000 Ljubljana Slovenia

Multi-label learning has received significant attention in the research community over the past few years: this has resulted in the development of a variety of multi-label learning methods. In this paper, we present an extensive experimental comparison of 12 multi-label learning methods using 16 evaluation measures over 11 benchmark datasets. We selected the competing methods based on their previous usage by the community, the representation of different groups of methods and the variety of basic underlying machine learning methods. Similarly, we selected the evaluation measures to be able to assess the behavior of the methods from a variety of view-points. In order to make conclusions independent from the application domain, we use 11 datasets from different domains. Furthermore, we compare the methods by their efficiency in terms of time needed to learn a classifier and time needed to produce a prediction for an unseen example. We analyze the results from the experiments using Friedman and Nemenyi tests for assessing the statistical significance of differences in performance. The results of the analysis show that for multi-label classification the best performing methods overall are random forests of predictive clustering trees (RF-PCT) and hierarchy of multi-label classifiers (HOMER), followed by binary relevance (BR) and classifier chains (CC). Furthermore, RF-PCT exhibited the best performance according to all measures for multi-label ranking. The recommendation from this study is that when new methods for multi-label learning are proposed, they should be compared to RF-PCT and HOMER using multiple evaluation measures. © 2012 Elsevier Ltd. All rights reserved.

关键词： Learning systems

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A hybrid optimization algorithm for the multi-chromosomal reversal median problem

A hybrid optimization algorithm for the multi-chromosomal re...

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1st International Conference on engineering and Technology Innovation, ICETI 2011

作者： Zhang, Yi Zhang, Meng Department of Computer Science Jilin Business and Technology College Changchun 130062 China Military Simulation Technology Institute Air Force Aviation University Changchun130022 China Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun 130012 China

ISBN: (纸本)9783037853245

In this paper, we introduce a hybrid optimization algorithm with the Branch-and-Bound Method and the Ant Colony Optimization to solve the multi-chromosomal reversal median problem. We convert the large-scale genome into TSP maps at first. Then we use a hybrid optimization algorithm with the Branch-and-Bound Method and the Ant Colony Optimization to solve the problem. In our improved algorithm, we increase the search speed by implement multi-branch parallel search of ACO. Our extensive experiments on simulated datasets show that this median solver is efficient.

关键词： Ant colony optimization

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