International Journal of Intelligent Information and Database Systems http://www.inderscience.com/browse/index.php?journalID=209&year=2012&vol=6&issue=1 Inderscience Publishers Ltd en-uk International Journal of Intelligent Information and Database Systems 1751-5858 1751-5866 © 2012 Inderscience Publishers Ltd editor@inderscience.com https://www.inderscience.com/images/files/coverImgs/ijiids_scoverijiids.jpg http://www.inderscience.com/browse/index.php?journalID=209&year=2012&vol=6&issue=1 http://www.inderscience.com/link.php?id=45113 XML Publish/Subscribe systems are system-active and user-passive systems that asynchronously serve users' queries. These queries are usually stored and later executed when matching XML documents become available. With large amounts of subscriptions and in the presence of sharable queries, efficient execution of these queries becomes a substantial requirement. In this work, we describe a novel approach that uses new physical algebra which is capable of handling a group of sharable queries that are submitted against streaming and/or stored XML documents. Our grouping approach is designed to share computations and eliminate redundant executions by producing a single algebraic query execution plan (QEP) for all resident queries and sharing execution in composed physical operators. To assess the effectiveness of our approach, we designed and implemented the physical algebra operators in a system which we then used to conduct experiments that helped us to compare between processing a single query and that of group of queries. Details of our proposed approach, the design and implementation of the related system and the results of our experimental study are presented in this article, together with a discussion of planned directions of future work. Handling sharable queries in both streaming and stored XML documents
Marcel Karam; Rana Awada
International Journal of Intelligent Information and Database Systems, Vol. 6, No. 1 (2012) pp. 3 - 29
XML Publish/Subscribe systems are system-active and user-passive systems that asynchronously serve users' queries. These queries are usually stored and later executed when matching XML documents become available. With large amounts of subscriptions and in the presence of sharable queries, efficient execution of these queries becomes a substantial requirement. In this work, we describe a novel approach that uses new physical algebra which is capable of handling a group of sharable queries that are submitted against streaming and/or stored XML documents. Our grouping approach is designed to share computations and eliminate redundant executions by producing a single algebraic query execution plan (QEP) for all resident queries and sharing execution in composed physical operators. To assess the effectiveness of our approach, we designed and implemented the physical algebra operators in a system which we then used to conduct experiments that helped us to compare between processing a single query and that of group of queries. Details of our proposed approach, the design and implementation of the related system and the results of our experimental study are presented in this article, together with a discussion of planned directions of future work.

]]> 10.1504/IJIIDS.2012.045113 International Journal of Intelligent Information and Database Systems, Vol. 6, No. 1 (2012) pp. 3 - 29 Marcel Karam; Rana Awada Department of Computer Science, American University of Beirut, Bliss 318 – 11-0236, Beirut, Lebanon. ' School of Information Technology and Engineering (SITE), University of Ottawa, 800 King Edward St. Ottawa, Ontario, K1N 6N5, Canada XML XPath query execution plans QEP physical algebra sharable queries streaming XML documents stored XML documents. 2012-01-27T23:20:50-05:00 6 1 3 29 2012-01-27T23:20:50-05:00 http://www.inderscience.com/link.php?id=45114 Ranking of help functions with respect to their usefulness is in the main focus of this work. A help function is regarded as useful to a student if the student has succeeded to solve a problem after using it. Methods from the theory of partial orderings are further applied facilitating an automated process of suggesting individualised advises on how to proceed in order to solve a particular problem. The decision making process is based on the common assumption that if given a choice between two alternatives, a person will choose one. Thus, obtained partial orderings appeared to be all linear orders since each pair of alternatives is compared. In this paper, we propose ranking help functions in an intelligent tutoring system with respect to their usefulness. Automated decision making based on weak orderings
Sylvia Encheva
International Journal of Intelligent Information and Database Systems, Vol. 6, No. 1 (2012) pp. 30 - 44
Ranking of help functions with respect to their usefulness is in the main focus of this work. A help function is regarded as useful to a student if the student has succeeded to solve a problem after using it. Methods from the theory of partial orderings are further applied facilitating an automated process of suggesting individualised advises on how to proceed in order to solve a particular problem. The decision making process is based on the common assumption that if given a choice between two alternatives, a person will choose one. Thus, obtained partial orderings appeared to be all linear orders since each pair of alternatives is compared. In this paper, we propose ranking help functions in an intelligent tutoring system with respect to their usefulness.

]]> 10.1504/IJIIDS.2012.045114 International Journal of Intelligent Information and Database Systems, Vol. 6, No. 1 (2012) pp. 30 - 44 Sylvia Encheva Faculty of Technology, Business and Maritime Sciences, Stord/Haugesund University College, Bjørnsonsg, 45, 5528 Haugesund, Norway decision support systems DSS uncertainty management partial orderings automated decision making weak orderings help functions problem solving intelligent tutoring systems ITS. 2012-01-27T23:20:50-05:00 6 1 30 44 2012-01-27T23:20:50-05:00 http://www.inderscience.com/link.php?id=45116 Due to the lateral gene transfer, the phylogenetic tree could be inadequate for representing the evolution of virus. This paper employs the distance invariant manifold (Cheng and Liou, 2009) to display the collection of influenza A in a cubic space. This space provides a global view of the evolution of the whole family vividly. Visualisation of influenza A protein segments in distance invariant self-organising map
Wei-Chen Cheng; Cheng-Yuan Liou
International Journal of Intelligent Information and Database Systems, Vol. 6, No. 1 (2012) pp. 45 - 60
Due to the lateral gene transfer, the phylogenetic tree could be inadequate for representing the evolution of virus. This paper employs the distance invariant manifold (Cheng and Liou, 2009) to display the collection of influenza A in a cubic space. This space provides a global view of the evolution of the whole family vividly.

]]> 10.1504/IJIIDS.2012.045116 International Journal of Intelligent Information and Database Systems, Vol. 6, No. 1 (2012) pp. 45 - 60 Wei-Chen Cheng; Cheng-Yuan Liou Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan. ' Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan information visualisation tree of life self-organising maps distance invariant manifold influenza A H1N1 avian influenza bird flu H5N1 phylogenetic tree lateral gene transfer mutation. 2012-01-27T23:20:50-05:00 6 1 45 60 2012-01-27T23:20:50-05:00 http://www.inderscience.com/link.php?id=45117 The goal of this paper is to describe a method to automatically extract all basic attributes namely actor, action, object, time and location which belong to an activity from Japanese weblogs. Sentences retrieved from weblogs are often diversified, complex, syntactically wrong, have emoticons and new words. There are some works that have tried to extract users' activities in sentences retrieved from web and weblogs. However, these works have several limitations, such as inability of extracting infrequent activities, high setup cost, limitation on the types of sentences that can be handled, necessary of preparing a list of object and action. To resolve these problems, we propose a novel approach that treats the activity extraction as a sequence labelling problem, and automatically makes its own training data. This approach can extract infrequent activities, and has advantages such as scalability, and unnecessary any hand-tagged data. Since it does not require to fix the positions and the number of the attributes in activity sentences, this approach can extract all attributes, with high recall. Self-supervised capturing of users' activities from weblogs
The-Minh Nguyen; Takahiro Kawamura; Yasuyuki Tahara; Akihiko Ohsuga
International Journal of Intelligent Information and Database Systems, Vol. 6, No. 1 (2012) pp. 61 - 76
The goal of this paper is to describe a method to automatically extract all basic attributes namely actor, action, object, time and location which belong to an activity from Japanese weblogs. Sentences retrieved from weblogs are often diversified, complex, syntactically wrong, have emoticons and new words. There are some works that have tried to extract users' activities in sentences retrieved from web and weblogs. However, these works have several limitations, such as inability of extracting infrequent activities, high setup cost, limitation on the types of sentences that can be handled, necessary of preparing a list of object and action. To resolve these problems, we propose a novel approach that treats the activity extraction as a sequence labelling problem, and automatically makes its own training data. This approach can extract infrequent activities, and has advantages such as scalability, and unnecessary any hand-tagged data. Since it does not require to fix the positions and the number of the attributes in activity sentences, this approach can extract all attributes, with high recall.

]]> 10.1504/IJIIDS.2012.045117 International Journal of Intelligent Information and Database Systems, Vol. 6, No. 1 (2012) pp. 61 - 76 The-Minh Nguyen; Takahiro Kawamura; Yasuyuki Tahara; Akihiko Ohsuga Graduate School of Information Systems, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu-shi, Tokyo 182-8585, Japan. ' Graduate School of Information Systems, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu-shi, Tokyo 182-8585, Japan. ' Graduate School of Information Systems, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu-shi, Tokyo 182-8585, Japan. ' Graduate School of Information Systems, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu-shi, Tokyo 182-8585, Japan human activities semantic networks weblogs weblog mining self-supervised learning conditional random fields blogs blog mining Japan user attributes activity extraction sequence labelling infrequent activities attribute extraction. 2012-01-27T23:20:50-05:00 6 1 61 76 2012-01-27T23:20:50-05:00 http://www.inderscience.com/link.php?id=45115 The paper presents a method of parameters estimation for artificial neural network based on fuzzy inference system (ANNBFIS). It is based on deterministic annealing, ε-insensitive learning by solving a system of linear inequalities and robust fuzzy c-means clustering. The proposed algorithm allows to improve the neuro-fuzzy modelling quality by increasing the generalisation ability and outliers robustness. To find the unknown number of fuzzy rules we proposed the procedure of robust clusters merging. The performance of the learning method is demonstrated through the benchmark sunspot prediction problem. Robust extraction of fuzzy rules with artificial neural network based on fuzzy inference system
Robert Czabanski; Michal Jezewski; Janusz Jezewski; Janusz Wrobel; Krzysztof Horoba
International Journal of Intelligent Information and Database Systems, Vol. 6, No. 1 (2012) pp. 77 - 92
The paper presents a method of parameters estimation for artificial neural network based on fuzzy inference system (ANNBFIS). It is based on deterministic annealing, ε-insensitive learning by solving a system of linear inequalities and robust fuzzy c-means clustering. The proposed algorithm allows to improve the neuro-fuzzy modelling quality by increasing the generalisation ability and outliers robustness. To find the unknown number of fuzzy rules we proposed the procedure of robust clusters merging. The performance of the learning method is demonstrated through the benchmark sunspot prediction problem.

]]> 10.1504/IJIIDS.2012.045115 International Journal of Intelligent Information and Database Systems, Vol. 6, No. 1 (2012) pp. 77 - 92 Robert Czabanski; Michal Jezewski; Janusz Jezewski; Janusz Wrobel; Krzysztof Horoba Institute of Electronics, Silesian University of Technology, ul. Akademicka 16, 44-101 Gliwice, Poland. ' Institute of Electronics, Silesian University of Technology, ul. Akademicka 16, 44-101 Gliwice, Poland. ' Department of Signal Processing, Institute of Medical Technology and Equipment, ul. Roosevelta 118, 41-800 Zabrze, Poland. ' Department of Signal Processing, Institute of Medical Technology and Equipment, ul. Roosevelta 118, 41-800 Zabrze, Poland. ' Department of Signal Processing, Institute of Medical Technology and Equipment, ul. Roosevelta 118, 41-800 Zabrze, Poland fuzzy rules extraction signal prediction neuro-fuzzy systems robust methods artificial neural networks ANNs fuzzy inference systems linear inequalities fuzzy c-means clustering modelling sunspot prediction. 2012-01-27T23:20:50-05:00 6 1 77 92 2012-01-27T23:20:50-05:00