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A practice probability frequent pattern mining method over transactional uncertain data streams

A practice probability frequent pattern mining method over t...

引用

Lecture Notes in computer science

作者： Liao, Guoqiong Wu, Linqing Wan, Changxuan Xiong, Naixue School of Information Technology Jiangxi University of Finance and Economics Nanchang 330013 China Jiangxi Key Laboratory of Data and Knowledge Engineering Nanchang 330013 China Department of Computer Science Georgia State University United States

ISBN: (纸本)9783642236402

In recent years, large amounts of uncertain data are emerged with the widespread employment of the new technologies, such as wireless sensor networks, RFID and privacy protection. According to the features of the uncertain data streams such as incomplete, full of noisy, non-uniform and mutable, this paper presents a probability frequent pattern tree called PFP-tree and a method called PFP-growth, to mine probability frequent patterns based on probability damped windows. The main characteristics of the suggested method include: (1) adopting time-based probability damped window model to enhance the accuracy of mined frequent patterns;(2) setting an item index table and a transaction index table to speed up retrieval on the PFP-tree;and (3) pruning the tree to remove the items that cannot become frequent patterns;. The experimental results demonstrate that PFP-growth method has better performance than the main existing schemes in terms of accuracy, processing time and storage space. © 2011 Springer-Verlag.

关键词： Probability

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An efficient pre-processing method to identify logical components from PDF documents

An efficient pre-processing method to identify logical compo...

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作者： Liu, Ying Bai, Kun Gao, Liangcai Department of Knowledge Service Engineering KAIST Korea Republic of IBM Research T.J. Watson Research Center United States Institute of Computer Science and Technology Peking University China

ISBN: (纸本)9783642208409

As the rapid growth of the scientific documents in digital libraries, the search demands for the documents as well as specific components increase dramatically. Accurately detecting the component boundary is of vital importance to all the further information extraction and applications. However, document component boundary detection (especially the table, figure, and equation) is a challenging problem because there is no standardized formats and layouts across diverse documents. This paper presents an efficient document preprocessing technique to improve the document component boundary detection performance by taking advantage of the nature of document lines. Our method easily simplifies the component boundary detection problem into the sparse line analysis problem with much less noise. We define eight document line label types and apply machine learning techniques as well as the heuristic rule-based method on identifying multiple document components. Combining with different heuristic rules, we extract the multiple components in a batch way by filtering out massive noises as early as possible. Our method focus on an important un-tagged document format - PDF documents. The experimental results prove the effectiveness of the sparse line analysis. © 2011 Springer-Verlag.

关键词： Digital libraries

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A heuristic genetic process mining algorithm

A heuristic genetic process mining algorithm

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2011 7th International Conference on Computational Intelligence and Security, CIS 2011

作者： Li, Jiafei Ouyang, Jihong Liu, Jiafei Ouyeng, Jihong Feng, Mingyong Department of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Industry Applications Department Cattsoft Technology Co. Ltd. Beijing China

ISBN: (纸本)9780769545844

The current GPM algorithm needs many iterations to get good process models with high fitness which makes the GPM algorithm usually time-consuming and sometimes the result can not be accepted. To mine higher quality model in shorter time, a heuristic solution by adding log-replay based crossover operator and direct/indirect dependency relation based mutation operator is put forward. Experiment results on 25 benchmark logs show encouraging results. © 2011 IEEE.

关键词： Data mining

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Convergence of algorithms for solving the Nearest Point Problem in Reduced Convex Hulls

Convergence of algorithms for solving the Nearest Point Prob...

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International Joint Conference on Neural Networks (IJCNN)

作者： Jorge López José R. Dorronsoro Department of Computer Science and the Knowledge Engineering Institute (IIC) Universidad Autónoma de Madrid Spain

In this paper we establish a framework for the convergence of two algorithms for solving the Nearest Point Problem in Reduced Convex Hulls (RCH-NPP), namely the RCH-GSK method proposed in [1] and the RCH-MDM method suggested in [2]. This framework allows us to show the asymptotic convergence of both methods in a very simple way. Moreover, it allows to justify a shrinking strategy for RCH-MDM.

关键词： Convergence Support vector machines Equations Cognition Sorting Buildings Writing

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MovieCommenter: Aspect-based collaborative filtering by utilizing user comments

MovieCommenter: Aspect-based collaborative filtering by util...

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International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom)

作者： Minsam Ko Hyung W. Kim Mun Y. Yi Junehwa Song Ying Liu Department of Knowledge Service Engineering KAIST Daejeon South Korea Department of Computer Science KAIST Daejeon South Korea

Collaborative filtering relies on numerical ratings for recommendations. While users consider various aspects of content as a basis of their evaluation, a numeric rating provides only an aggregated report of final assessment. The performance of a collaborative recommender system could be enhanced if the ratings are augmented by more specific information used for evaluation. In this paper, we present MovieCommenter, a recommender system that utilizes movie aspects - key features and users' opinions about the movie. We conducted a series of experiments to perform both qualitative and quantitative evauations of the system performance. The results show that our approach makes more precise recommendations than traditional approaches. Moreover, the interface of MovieCommenter was found to enhance the recommendation explanability, ability to explain how the recommendation was made. Because our approach is based on independent schema, this approach could be easily applied for recommending other domain contents.

关键词： Motion pictures Collaboration Feature extraction Manuals System performance Recommender systems computers

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A comparison of content-based tag recommendations in folksonomy systems

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Lecture Notes in computer science

作者： Illig, Jens Hotho, Andreas Jäschke, Robert Stumme, Gerd Knowledge and Data Engineering Group Department of Mathematics and Computer Science University of Kassel Wilhelmshöher Allee 73 34121 Kassel Germany Research Center L3S Appelstraße 9a 30167 Hannover Germany

ISBN: (纸本)9783642221392

Recommendation algorithms and multi-class classifiers can support users of social bookmarking systems in assigning tags to their bookmarks. Content based recommenders are the usual approach for facing the cold start problem, i.e., when a bookmark is uploaded for the first time and no information from other users can be exploited. In this paper, we evaluate several recommendation algorithms in a cold-start scenario on a large real-world dataset. © 2011 Springer-Verlag.

关键词： computers

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A study in the expressiveness of semantically different policy modelling schemes

A study in the expressiveness of semantically different poli...

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IFIP/IEEE International Symposium on Integrated Network Management

作者： Christos Tsarouchis Declan O'Sullivan David Lewis Knowledge & Data Engineering Group (KDEG) Department of Computer Science & Statistics Trinity College Dublin Dublin Ireland

ISBN: (纸本)9781424492190

Policy engineering is the process of authoring IT management policies, detecting and resolving policy conflicts and revising existing policies to accommodate changing IT resources, business goals and business processes. Policy authoring is often followed by policy enforcement where the actions specified by subjects are performed on targets (resources). In this paper, we study the use of semantically enhanced techniques, such as ontologies, to model resources and their corresponding actions, coupled with a mechanism that can accommodate frequent organizational change, to model policy subjects. For the modeling of policy subjects, the rule-based Community-based Policy management will be used. This integration falls into the category of combining Description Logics (DL) and Logic Programs (LP). We aim to study this integration primarily from the scope of overall system expressivity, but also from the scope of minimizing the cognitive load perceived by policy authors. Such an evaluation can help determine shortfalls in the design of the software system or of the policy model used. To study the balance in modeling with DL and LP techniques, the encoding of part of the Trinity College Dublin statutes will be performed, which is a sufficiently complex real-world example.

关键词： OWL Load modeling Ontologies Welding Analytical models Security Fires

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Hybrid classifiers for improved semantic subspace learning of news documents

Hybrid classifiers for improved semantic subspace learning o...

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2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011

作者： Tripathi, Nandita Oakes, Michael Wermter, Stefan Department of Computing Engineering and Technology University of Sunderland St Peters Way Sunderland SR6 0DD United Kingdom Institute for Knowledge Technology Department of Computer Science University of Hamburg Vogt Koelln Str. 30 22527 Hamburg Germany

ISBN: (纸本)9781457721502

The volume and diversity of documents available in today's world is increasing daily. It is therefore difficult for a single classifier to efficiently handle multi-level categorization of such a varied document space. In this paper we analyse methods to enhance the efficiency of a single classifier for two-level classification by combining it with classifiers of other types. We use the maximum significance value as an indicator for the subspace of a test document. We represent the documents using the conditional significance vector which increases the distinction between classes within a subspace. Our experiments show that dividing a document space into different semantic subspaces increases the efficiency of such hybrid classifier combinations. Applying different types of classifiers on different subspaces substantially improves overall learning. © 2011 IEEE.

关键词： Efficiency

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Bow-tie decomposition in directed graphs

Bow-tie decomposition in directed graphs

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International Conference on Information Fusion

作者： Rong Yang Leyla Zhuhadar Olfa Nasraoui Department of Mathematics and Computer Science Western Kentucky University Bowling Green KY USA Knowledge Discovery and Web Mining Laboratory Department of Computer Engineering and Computer Science University of Louisville KY USA

ISBN: (纸本)9781457702679

The bow-tie structure is frequently cited in the literature of the World Wide Web and in many other areas, such as metabolic networks, but it has never been precisely defined, so that to some extent the concept being discussed remains vague. This paper first provides a formal definition of a bow-tie structure relative to a given strongly connected components. That definition details distinctions which are not usually made, such as the difference between intendrils and outtendrils. Theorems and algorithms are then provided to justify and support the definition. Finally a bow-tie decomposition algorithm is developed and illustrated. The algorithms have also been implemented and tested on a university domain.

关键词： Algorithm design and analysis Electron tubes Web sites Social network services Computational modeling Biochemistry Communities

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Constant approximation for virtual backbone construction with Guaranteed Routing Cost in wireless sensor networks

Constant approximation for virtual backbone construction wit...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Hongwei Du Qiang Ye Weili Wu Wonjun Lee Deying Li Dingzhu Du Stephen Howard Department of Computer Science and Information Technology University of Prince Edward Island Canada Department of Computer Science University of Texas Dallas USA Department of Computer Science and Engineering Korea University Seoul South Korea Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China China

ISBN: (纸本)9781424499199

In wireless sensor networks, virtual backbone construction based on connected dominating set is a competitive issue for routing efficiency and topology control. Assume that a sensor networks is defined as a connected unit disk graph (UDG). The problem is to find a minimum connected dominating set of given UDG with minimum routing cost for each node pair. We present a constant approximation scheme which produces a connected dominating set D, whose size |D| is within a factor α from that of the minimum connected dominating set and each node pair exists a routing path with all intermediate nodes in D and with length at most 5 · d(u,v), where d(u,v) is the length of shortest path of this node pair. A distributed algorithm is also provided with analogical performance. Extensive simulation shows that our distributed algorithm achieves significantly than the latest solution in research direction.

关键词： Routing Approximation methods Distributed algorithms Wireless sensor networks Polynomials computer science Electronic mail

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