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Capturing application-domain specific patterns in a Web application: the e-learning paradigm

Capturing application-domain specific patterns in a Web appl...

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4th IASTED international conference on Web-Based Education, WBE 2005

作者： Dimitrakopoulou, Dimitra Rigou, Maria Sirmakessis, Spiros Tsakalidis, Athanasios Tzimas, Giannis Research Academic Computer Technology Institute Internet and Multimedia Technologies Research Unit 61 Riga Feraiou str. GR-262 21 Patras Hellas Greece University of Patras Computer Engineering and Informatics Department GR-26504 Rio-Patras Hellas Greece Technological Educational Institution of Messolongi Nea Ktiria GR-30200 Messolongi Hellas Greece

ISBN: (纸本)0889864802

Designing and maintaining Web applications is one of the major challenges that software industry has to face. Several modeling techniques have been proposed to support this process. In this work we present a methodology for identifying design patterns within an application modelled using WebML, a modelling language for designing data-intensive Web applications. We extend the set of design patterns supported by WebML and exemplify the application of the methodology using an e-learning scenario.

关键词： E-learning

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Some studies on Chinese domain knowledge dictionary and its application to text classification 4

Some studies on Chinese domain knowledge dictionary and its ...

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4th SIGHAN Workshop on Chinese Language Processing at the 2nd international Joint conference on Natural Language Processing, SIGHAN@IJCNLP 2005

作者： Zhu, Jingbo Chen, Wenliang Natural Language Processing Lab Institute of Computer Software and Theory Northeastern University Shenyang China

In this paper, we study some issues on Chinese domain knowledge dictionary and its application to text classification task. First a domain knowledge hierarchy description framework and our Chinese domain knowledge dictionary named NEUKD are introduced. Second, to alleviate the cost of construction of domain knowledge dictionary by hand, we use a boostrapping-based algorithm to learn new domain associated terms from a large amount of unlabeled data. third, we propose two models (BOTW and BOF) which use domain knowledge as textual features for text categorization. But due to limitation of size of domain knowledge dictionary, we further study machine learning technique to solve the problem, and propose a BOL model which could be considered as the extended version of BOF model. Naïve Bayes classifier based on BOW model is used as baseline system in the comparison experiments. Experimental results show that domain knowledge is very useful for text categorization, and BOL model performs better than other three models, including BOW, BOTW and BOF models. © 2005 SIGHAN@IJCNLP 2005 - 4th SIGHAN Workshop on Chinese Language Processing, proceedings of the Workshop. All Rights Reserved.

关键词： Domain Knowledge

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learning to extract genic interactions using gleaner

Learning to extract genic interactions using gleaner

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4th Workshop on learning Language in Logic, LLL 2005, Part of the 22nd international conference on machine learning, ICML 2005

作者： Goadrich, Mark Oliphant, Louis Shavlik, Jude Department of Biostatistics and Medical Informatics and Department of Computer Sciences University of Wisconsin-Madison Madison WI 53706 United States

We explore here the application of Gleaner, an Inductive Logic Programming approach to learning in highly-skewed domains, to the learning Language in Logic 2005 biomedical information-extraction challenge task. We create and describe a large number of background knowledge predicates suited for this task. We find that Gleaner outperforms standard Aleph theories with respect to recall and that additional linguistic background knowledge improves recall.

关键词： Inductive logic programming (ILP)

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Prediction of secondary protein structure content from primary sequence alone - A feature selection based approach

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4th international conference on machine learning and Data Mining in Pattern Recognition

作者： Kurgan, L Homaeian, L Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2V4 Canada

ISBN: (纸本)3540269231

Research in protein structure and function is one of the most important subjects in modem bioinformatics and computational biology. It often uses advanced data mining and machine learning methodologies to perform prediction or pattern recognition tasks. this paper describes a new method for prediction of protein secondary structure content based on feature selection and multiple linear regression. the method develops a novel representation of primary protein sequences based on a large set of 495 features. the feature selection task performed using very large set of nearly 6,000 proteins, and tests performed on standard non-homologues protein sets confirm high quality of the developed solution. the application of feature selection and the novel representation resulted in 14-15% error rate reduction when compared to results achieved when standard representation is used. the prediction tests also show that a small set of 5-25 features is sufficient to achieve accurate prediction for both helix and strand content for non-homologous proteins.

关键词： Proteins

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Lumping of atmospheric chemical species by machine learning 4

Lumping of atmospheric chemical species by machine learning

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4th international conference on Environmental Informatics, ISEIS 2005

作者： Polam, Pruthvi Mandy, Margot E. Brown, Charles G. University of Northern British Columbia 3333University Way Prince GeorgeBCV2N 4Z9. Canada

An atmospheric chemical mechanism is a detailed description of a sequence of reactions which summarizes the relevant chemical pathways and gives certain, essentially qualitative, information about the fate of atmospheric chemical species. Several chemical mechanisms have been proposed for regional air quality models. the atmospheric chemical mechanisms are the most computationally intensive components of the photochemical air quality simulation models. Lumping of atmospheric chemical species into different groups is one of the effective techniques used to reduce the complexity of the reaction mechanisms. this paper deals with the development of a system which is used to lump the atmospheric hydrocarbons into different groups by a functional group approach. Since lumping of chemical species into different categories is a classification problem, we have identified from the computational prospective that the application of machine learning by Artificial Neural Networks (ANN) as appropriate to solve the problem. the conventional notation used to represent chemical species is not in a form which can be given directly as an input for the machine learning. SMILES notation (Weininger, 1988. Journal of Chemical Information and computer Science. 28, 31-36) is used to represent the chemical species and can be converted to an internal Bond-Electron (BE) connectivity matrix notation (cf. Broadbelt, 1994. Industrial & Engineering Chemistry Research. 33, 790-799 ) which describes the connectivity of atoms within the molecule. the outputs in the output layer of the ANN are the lumped categories desired. We also consider the issues such as what type of chemical information is appropriate and how best to give this chemical information as input for ANN to obtain accurate results in classifying the chemical species into different lumped patterns. © 2005 ISEIS - international Society for Environmental Information Sciences.

关键词： Air quality

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Knowledge acquisition through machine learning: Minimising expert's effort

Knowledge acquisition through machine learning: Minimising e...

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ICMLA 2005: 4th international conference on machine learning and applications

作者： Blanco-Vega, Ricardo Hernández-Orallo, José Ramíez-Quintana, María José Dep. de Sist. Informáticos y Computación Universidad Politécnica de Valencia C. de Vera s/n 46022 Valencia Spain

ISBN: (纸本)0769524958

machine learning can be applied to solve the knowledge acquisition bottleneck in many areas where an expert makes predictions to single cases, such as diagnosis, estimation, etc. the idea is to query the expert with as many cases as possible and get their answers. With this data we train a machine learning model which mimics the expert's behaviour. this is just a simple application of a modelling technique known as "mimetism", which has many other applications. this "soft" approach to knowledge acquisition has many advantages: any machine learning technique can be used, the expert must only answer simple questions (cases) and we can combine the decisions of several experts easily. However, one problem of this approach is that we do not know in advance how many cases we will need to ask in order to get a good model which is accurate wrt. the expert's knowledge. Obviously, as more data is labelled by the expert better results are obtained. However, asking thousands of cases to the expert is usually impractical. In this paper, we analyse the behaviour of knowledge acquisition through mimetic learning according to two factors: accuracy and comprehensibility of the resulting model and we devise a method to compute the minimum number of cases that we need to ask the expert to attain a certain quality level. © 2005 IEEE.

关键词： Knowledge acquisition

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Coordinated exploration in multi-agent reinforcement learning: An application to load-balancing

Coordinated exploration in multi-agent reinforcement learnin...

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4th international conference on Autonomous Agents and Multi agent Systems, AAMAS 05

作者： Verbeeck, Katja Nowé, Ann Tuyls, Karl Computational Modeling Lab Vrije Universiteit Brussel Pleinlaan 2 1050 Brussel Belgium Theoretical Computer Science Group University of Limburg Diepenbeek Belgium

this paper is concerned with how multi-agent reinforcement learning algorithms can practically be applied to real-life problems. Recently, a new coordinated multi-agent exploration mechanism, called Exploring Selfish Reinforcement learning (ESRL) was proposed. With this mechanism, a group of independent agents can find optimal fair solutions in multi-agent problems, without the need for modeling other agents, without the need of knowing the type of the multiagent problem confronted with and by using only a limited form of communication. In particular, the mechanism allows for using natural reinforcement signals coming from the application itself. We report on how ESRL agents can solve the problem of load-balancing in a natural way, both as a common interest and as a conflicting interest problem. Copyright 2005 ACM.

关键词： Multi agent systems

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LQ-routing protocol for mobile ad-hoc networks 05

LQ-routing protocol for mobile ad-hoc networks

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4th Annual international conference on computer and Information Science (ICIS 2005)

作者： Tao, T Tagashira, S Fujita, S Hiroshima Univ Grad Sch Engn Dept Informat Engn Higashihiroshima Japan

ISBN: (纸本)0769522963

In this paper, we propose a new routing protocol for mobile ad-hoc networks (MANET), which have attracted considerable attentions in recent years as a tool to realize flexible and robust communication environments in many critical application fields. the proposed protocol, called LQ-routing, is a proactive routing protocol based on the Q-routing protocol which was originally proposed for conventional wired networks. In order to reflect the mobility of hosts to the routing decision, which would cause frequent connection and disconnection of communication links between nearby hosts, we introduce the notion of lifetime to represent the stability of routes connecting to the destination. the performance of the proposed routing scheme is experimentally evaluated by using NS-2. the result of simulation indicates that by introducing the notion of lifetime to a simple combination of previous proactive routing scheme DSDV and the Q-routing, we could improve the performance of DSDV in terms of the packet loss rate and the average packet delay.

关键词： mobile ad hoc network routing reinforcement learning DSDV Q-routing

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Conceptual framework of computer-supported Ubiquitous learning Environment

Conceptual framework of computer-supported Ubiquitous Learni...

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4th IASTED international conference on Web-Based Education, WBE 2005

作者： Li, Luyi Zheng, Yanlin Ogata, Hiroaki Yano, Yoneo Dept. of Information Science and Intelligent Systems Faculty of Engineering Tokushima University Japan

ISBN: (纸本)0889864802

this paper proposes a conceptual framework for Ubiquitous learning Environment (ULE) construction. ULE is integrated from multi-dimensions, such as physical, social, informational and technical settings, where schools, communities, and families will be integrated in a smooth context. ULE is established on the combination between Real World and Virtual Space, Personal Space and Shared Space. learning in ULE is conducted in the interactions among three essential communicative elements: Social Human, Object in real world, and Artifact in virtual space. learning process is a social transfer process between tacit and explicit knowledge. Context-Awareness is indispensable to all kinds of interactions in ULE. Especially, this paper gives a discussion to context-awareness supported Interoperability and Adaptability in ULE. Additionally, this paper also gives a simple reminder to related learning terms, Blended learning, Social and Emotional learning, Service-learning, and Situated learning, which are contributive to our deeper understanding to learning in ULE. On practical dimension, this paper presents a design framework for ULE implementation by integrating the application of three kinds of affordable learning devices: networked PC, PDA, and mobile Phone.

关键词： Cellular telephones

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learning biological interactions from medline abstracts

Learning biological interactions from medline abstracts

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4th Workshop on learning Language in Logic, LLL 2005, Part of the 22nd international conference on machine learning, ICML 2005

作者： Katrenko, Sophia Scott Marshall, M. Roos, Marco Adriaans, Pieter Human-Computer Studies Laboratory University of Amsterdam Kruislaan 419 1098 VA Amsterdam Netherlands Integrative Bioinformatics Unit University of Amsterdam Kruislaan 318 1098 SM Amsterdam Netherlands

In this paper, we describe our approach to the Genic Interaction Extraction Challenge. Our solution combines several elements: 1) a domain theory about the interaction between language, semantics and syntax, 2) a biological ontology identifying amongst other things biomolecular entities and directed interaction verbs in the lexicon, 3) the notion of lexical-semantic-syntactic unification, 4) the notion of partial unification of lexicalsemantic syntactic trees and 5) the application of the standard RIPPER algorithm to the results. Using this approach on the very limited training and test data from the Challenge we show results that are promising. Our method observes a clear separation between domain-independent and domainspecific components. It can therefore easily be extended to other domains. We briey describe the implementation of the techniques, discuss the results and give suggestions for improvements and further results in the conclusion.

关键词： Syntactics

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