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A multi-heuristic cooperative ant colony system for optimizing elimination ordering of Bayesian networks

A multi-heuristic cooperative ant colony system for optimizi...

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2010 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2010

作者： Dong, Xuchu Ouyang, Dantong Ye, Yuxin Yu, Haihong Zhang, Yonggang Department of Computer Science and Technology Jilin University Changchun Jilin 130012 China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun Jilin 130012 China

ISBN: (纸本)9780769541914

To solve the problem of searching for an optimal elimination ordering of Bayesian networks, a novel effective heuristic, MinSumWeight, and an ACS approach incorporated with multi-heuristic mechanism are proposed. The ACS approach named MHC-ACS utilizes a set of heuristics to direct the ants moving in the search space. The cooperation of multiple heuristics helps ants explore more regions. Moreover, the most appropriate heuristic will be identified and be reinforced with the evolution of the whole system. Experiments demonstrate that MHC-ACS has a better performance than other swarm intelligence methods. © 2010 IEEE.

关键词： Bayesian networks

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Two novel semantics of top-k queries processing in uncertain database

Two novel semantics of top-k queries processing in uncertain...

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10th IEEE International Conference on computer and Information Technology, CIT-2010, 7th IEEE International Conference on Embedded Software and Systems, ICESS-2010, 10th IEEE Int. Conf. Scalable Computing and Communications, ScalCom-2010

作者： Liu, Dexi Wan, Changxuan Xiong, N. Yang, Laurence T. Chen, Lei Jiangxi Key Laboratory of Data and Knowledge Engineering School of Information Technology Jiangxi University of Finance and Economics Nanchang China Department of Computer Science Georgia State University Atlanta GA United States Department of Computer Science St. Francis Xavier University Antigonish NS Canada Department of Computer Science HK University of Science and Technology Hong Kong Hong Kong

ISBN: (纸本)9780769541082

Top-k query is a powerful technique in uncertain databases because of the existence of exponential possible worlds, and it is necessary to combine score and confidence of tuples to derive top k answers. Different semantics, the combination methods of score and confidence, lead to different results. U-kRanks and Global Top-k are two semantics of Topk queries in uncertain database, which consider every alternative in x-tuple as single one and return the tuple which has the highest probability appearing at top k or a given rank. However, no matter which alternative (tuple) of an x-tuple appears in a possible world, it undoubtedly believes that this xtuple appears in the same possible world accordingly. Thus, instead of ranking every individual tuple, we define two novel Top-k queries semantics in uncertain database, Uncertain xkRanks queries (U-x-kRanks) and Global x-Top-k queries (Gx- Top-k), which return k entities according to the score and the confidence of alternatives in x-tuple, respectively. In order to reduce the search space, we present an efficient algorithm to process U-x-kRanks queries and G-x-Top-k queries. Comprehensive experiments on different data sets demonstrate the effectiveness of the proposed solutions. © 2010 IEEE.

关键词： Semantics

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Mitigation of large-scale RDF data loading with the employment of a cloud computing service

Mitigation of large-scale RDF data loading with the employme...

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作者： Namgoong, Hyun Kumar, Harshit Kim, Hong-Gee Biomedical Knowledge Engineering Lab. Seoul National University Seoul Korea Republic of Department of Computer Science University of Suwon Hwaseong Korea Republic of

ISBN: (纸本)9789898425294

An expanding need for interoperability and structuralization of web data has made use of RDF (Resource Description Framework) plentiful. To guarantee a common usage of the data within various applications, several RDF stores providing data management services have been developed. Here, we represent a systematic approach to solve a late latency problem of data loading of the stores. It enables a fast loading performance for very large size of RDF data, and it is proven with an existing RDF store. This approach employs a cloud computing service and delegates preparation works to the machines which are temporarily borrowed at little payment. Our implementation for a native version of the Sesame RDF Repository was tested on LUBM 1000 University data (138 million triples), and it showed a local store loading time of 16.2 minutes with additional preparation time on a cloud service taking approximately an hour, which can be reduced by adding supplemental machines to the cluster.

关键词： Data warehouses

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SPARQL2XQuery 2.0: Supporting semantic-based queries over XML data

SPARQL2XQuery 2.0: Supporting semantic-based queries over XM...

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5th International Workshop on Semantic Media Adaptation and Personalization, SMAP 2010

作者： Stavrakantonakis, Ioannis Tsinaraki, Chrisa Bikakis, Nikos Gioldasis, Nektarios Christodoulakis, Stavros MUSIC TUC Technical University of Crete Greece Department of Information Engineering and Computer Science University of Trento Italy Knowledge and Database Systems Laboratory National Technical University of Athens Greece

ISBN: (纸本)9781424486007

The dominant standards in multimedia content and service description, namely the MPEG-7 and the MPEG-21, have been expressed in XML Schema syntax. In addition, ontologies that capture the semantics of these standards have been developed using the semantic web languages. Since different communities in the industry and the academia work and are familiar with the Semantic Web environment or the XML environment, a Schema mapping framework and a Query mapping framework are needed that will allow querying multimedia content and service descriptions in a uniform way in both the XML and Semantic Web environments. We present in this paper SPARQL2XQuery 2.0, a framework that allows expressing semantic queries on top of XML data through the translation of SPARQL queries in XQuery syntax. SPARQL2XQuery 2.0 may work with both existing ontologies and with automatically produced ones, formed according to our XS2OWL 2.0 transformation model. XS2-OWL 2.0 exploits the OWL 2.0 semantics and supports the new XML constructs introduced by XML Schema 1.1. © 2010 IEEE.

关键词： XML

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Complete 3D model reconstruction using two types of depth sensors

Complete 3D model reconstruction using two types of depth se...

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2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010

作者： Mu, Guangyu Liao, Miao Yang, Ruigang Ouyang, Dantong Xu, Zhiwen Guo, Xiaoxin Department of Computer Science and Technology Jilin University Changchun China College of Information Jilin University of Finance and Economics Changchun China Department of Engineering University of Kentucky Center for Visualization and Virtual Environment Lexington KY United States Department of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of MOE Changchun China

ISBN: (纸本)9781424465835

We propose a fast and simple application system of 3D model reconstruction. We acquire range images by using a combination of a regular camera and two types of depth sensors. The reconstruction of a 3D model consists of four key steps: (i) Initial alignment either feature tracking or the 4-points congruent sets algorithm is used to align surfaces captured at different frames. (ii)The iterative closest point (ICP) method is applied to further align the piecewise surfaces from the last step. (iii) The surfaces are merged into a whole 3D model by the volumetric method. (iv) In the refinement step, we fill holes and produce a complete 3D model that approximates the original model with robust repair of polygonal models. At last, we present the experimental results which show that the errors between our reconstructed model and the ground truth are less than 1%. ©2010 IEEE.

关键词： Iterative methods

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Detection of visual concepts and annotation of images using ensembles of trees for hierarchical multi-label classification

Detection of visual concepts and annotation of images using ...

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20th International Conference on Pattern Recognition, ICPR 2010

作者： Dimitrovski, Ivica Kocev, Dragi Loskovska, Suzana Džeroski, Sašo Department of Knowledge Technologies Jožef Stefan Institute Jamova cesta 39 1000 Ljubljana Slovenia Department of Computer Science Faculty of Electrical Engineering and Information Technology Karpoš bb 1000 Skopje Macedonia

ISBN: (纸本)3642177107

In this paper, we present a hierarchical multi-label classification system for visual concepts detection and image annotation. Hierarchical multi-label classification (HMLC) is a variant of classification where an instance may belong to multiple classes at the same time and these classes/labels are organized in a hierarchy. The system is composed of two parts: feature extraction and classification/annotation. The feature extraction part provides global and local descriptions of the images. These descriptions are then used to learn a classifier and to annotate an image with the corresponding concepts. To this end, we use predictive clustering trees (PCTs), which are able to classify target concepts that are organized in a hierarchy. Our approach to HMLC exploits the annotation hierarchy by building a single predictive clustering tree that can simultaneously predict all of the labels used to annotate an image. Moreover, we constructed ensembles (random forests) of PCTs, to improve the predictive performance. We tested our system on the image database from the ImageCLEF@ICPR 2010 photo annotation task. The extensive experiments conducted on the benchmark database show that our system has very high predictive performance and can be easily scaled to large number of visual concepts and large amounts of data. © 2010 Springer-Verlag.

关键词： Feature extraction

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Detection of visual concepts and annotation of images using predictive clustering trees

Detection of visual concepts and annotation of images using ...

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2010 Cross Language Evaluation Forum Conference, CLEF 2010

作者： Dimitrovski, Ivica Kocev, Dragi Loskovska, Suzana Džeroski, Sašo Department of Knowledge Technologies Jožef Stefan Institute Jamova cesta 39 Ljubljana1000 Slovenia Department of Computer Science Faculty of Electrical Engineering and Information Technology Karpoš bb Skopje1000 Macedonia

In this paper, we present a multiple targets classification system for visual concepts detection and image annotation. Multiple targets classification (MTC) is a variant of classification where an instance may belong to multiple classes at the same time. The system is composed of two parts: feature extraction and classification/annotation. The feature extraction part provides global and local descriptions of the images. These descriptions are then used to learn a classifier and to annotate an image with the corresponding concepts. To this end, we use predictive clustering trees (PCTs), which are capable to classify an instance to multiple classes at once, thus exploit the interactions that may occur among the different visual concepts (classes). Moreover, we constructed ensembles (random forests) of PCTs, to improve the predictive performance. We tested our system on the image database from the visual concept detection and annotation task part of ImageCLEF 2010. The extensive experiments conducted on the benchmark database show that our system has very high predictive performance and can be easily scaled to large number of images and visual concepts.

关键词： Feature extraction

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MCRNR: Fast computing of restricted nash responses by means of sampling

MCRNR: Fast computing of restricted nash responses by means ...

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作者： Ponsen, Marc Lanctot, Marc De Jong, Steven Department of Knowledge Engineering Maastricht University Maastricht Netherlands Department of Computer Science University of Alberta Edmonton AB Canada Computational Modeling Lab Vrije Universiteit Brussel Brussel Belgium

ISBN: (纸本)9781577354697

This paper presents a sample-based algorithm for the computation of restricted Nash strategies in complex extensive form games. Recent work indicates that regret-minimization algorithms using selective sampling, such as Monte-Carlo Counterfactual Regret Minimization (MCCFR), converge faster to Nash equilibrium (NE) strategies than their non-sampled counterparts which perform a full tree traversal. In this paper, we show that MCCFR is also able to establish NE strategies in the complex domain of Poker. Although such strategies are defensive (i.e. safe to play), they are oblivious to opponent mistakes. We can thus achieve better performance by using (an estimation of) opponent strategies. The Restricted Nash Response (RNR) algorithm was proposed to learn robust counter-strategies given such knowledge. It solves a modified game, wherein it is assumed that opponents play according to a fixed strategy with a certain probability, or to a regret-minimizing strategy otherwise. We improve the rate of convergence of the RNR algorithm using sampling. Our new algorithm, MCRNR, samples only relevant parts of the game tree. It is therefore able to converge faster to robust best-response strategies than RNR. We evaluate our algorithm on a variety of imperfect information games that are small enough to solve yet large enough to be strategically interesting, as well as a large game, Texas Hold'em Poker. Copyright © 2010, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Trees (mathematics)

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The scaffolding of a formal context

The scaffolding of a formal context

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7th International Conference on Concept Lattices and Their Applications, CLA 2010

作者： Doerfel, Stephan Knowledge and Data Engineering Group Department of Mathematics and Computer Science University of Kassel Wilhelmshöher Allee 73 34121 Kassel Germany Department of Mathematics Institute of Algebra Technical University of Dresden 01062 Dresden Germany

The scaffolding of a complete lattice L of finite length was introduced by Rudolf Wille in 1976 as a relative subsemilattice of L that can be constructed using subdirect decomposition. The lattice is uniquely defined by its scaffolding and can be reconstructed from it. Using bonds, we demonstrate how the scaffolding can be constructed from a given formal context and thereby extend the notion of the scaffolding to doubly founded lattices. Further, we explain the creation of a suitable graphical representation of the scaffolding from the context.

关键词： Scaffolds

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Intelligent hybrid architecture for tourism services

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作者： Almeida, Ana Coelho, Bruno Martins, Constantino GECAD Knowledge Engineering and Decision Support Group Australia Computer Science Department Institute of Engineering Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto 4200-072 Portugal

ISBN: (纸本)3642152856

This paper presents an artificial intelligence-based architecture to be used in various tourism services, namely the user modeling and recommender system components. Through the use of several machine learning techniques, such as linear models, neural networks, classification and even text mining, a hybrid and complete approach at understanding tourism application users is attained. To assess the advantages of the model, a specific prototype was created, including a complex user modeling process and an advanced and innovative recommender system. The system was tested in the scope of Oporto city, in Portugal. © 2010 IFIP.

关键词： Recommender systems

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