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IEEE International Conference on Computational science and engineering, CSE

作者： Bruno Coelho Constantino Martins Ana Almeida GECAD-Knowledge Engineering and Decision Support Group Computer Science Department Institute of Engineering Polytechnic of Porto Porto Portugal

This paper presents an undertaken research work about the development of an Adaptive Tourism Modeling System which attempts to correctly model a tourism Web application user profile. This paper will follow the methodology used behind the concept of the application, `User Modeling as a process', which consists of three specific modules in order to achieve a clear user modeling technology. The user representation module devises a collection of knowledge representation formalisms that co-exist in order to constitute the system's view of the user; the user reasoning module is responsible for the execution of several inference tasks as well as the generation of possibly new and valuable information about the user, using the latter module. The user concept that comes out of these two modules will ultimately be used by various kinds of application-level systems, namely a recommender system, therefore instantiating a project-dependent third module.

关键词： knowledge engineering Recommender systems Artificial intelligence computer science Adaptive systems Application software knowledge representation Adaptation model Monitoring Decision support systems

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Efficient Algorithm for Computing Link-Based Similarity in Real World Networks

Efficient Algorithm for Computing Link-Based Similarity in R...

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IEEE International Conference on Data Mining (ICDM)

作者： Yuanzhe Cai Gao Cong Xu Jia Hongyan Liu Jun He Jiaheng Lu Xiaoyong Du Key Laboratories of Data Engineering and Knowledge Engineering Ministry of Education China Department of Computer Science Renmin University of China China Department of Computer Science University of Aalborg Denmark Department of Management Science and Engineering Tsinghua University China

Similarity calculation has many applications, such as information retrieval, and collaborative filtering, among many others. It has been shown that link-based similarity measure, such as SimRank, is very effective in characterizing the object similarities in networks, such as the Web, by exploiting the object-to-object relationship. Unfortunately, it is prohibitively expensive to compute the link-based similarity in a relatively large graph. In this paper, based on the observation that link-based similarity scores of real world graphs follow the power-law distribution, we propose a new approximate algorithm, namely Power-SimRank, with guaranteed error bound to efficiently compute link-based similarity measure. We also prove the convergence of the proposed algorithm. Extensive experiments conducted on real world datasets and synthetic datasets show that the proposed algorithm outperforms SimRank by four-five times in terms of efficiency while the error generated by the approximation is small.

关键词： computer networks Collaboration Data engineering knowledge engineering computer science Iterative algorithms Filtering Data mining Helium computer science education

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An empirical study of an RFID mat sensor system in a group home

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Journal of Networks 2009年第2期4卷 133-139页

作者： Miura, Motoki Ito, Sadanori Takatsuka, Ryozo Sugihara, Taro Kunifuji, Susumu School of Knowledge Science Japan Advanced Institute of Science and Technology Japan Department of Computer and Information Sciences Graduate School of Engineering Tokyo University of Agriculture and Technology Japan

We have been developing an RFID (radio frequency identification) mat system to assist caregivers in a group home. In Japan, the number of group homes offering home-like care for elderly persons suffering from dementia has increased considerably. Even though the smaller number of people residing in a group home makes it suitable for family-like care, the scarcity of caregivers increases the burden, especially during the night. To augment caregiver attention, we developed floor mats with embedded RFID antennae and slippers with RFID tags. These can help caregivers be aware of the activities of persons suffering from dementia by specifying whether an individual has passed over a mat in a particular corridor. This not only helps the caregivers understand such persons by reviewing their activities but also keeps them informed about their current activities. We introduced the floor mats in a real group home and confirmed the feasibility of the system. In this study, we describe the system and lessons learned from our experiment. © 2009 ACADEMY PUBLISHER.

关键词： Floors

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Learning Discriminative Multi-scale and Multi-position LBP Features for Face Detection Based on Ada-LDA

Learning Discriminative Multi-scale and Multi-position LBP F...

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2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

作者： Kwang Ho An Myung Jin Chung So Hee Park Ki Young Moon Yun Su Chung Electrical Engineering and Computer Science Department Korea Advanced Institute of Science and Techn Knowledge-based Information Security & Safety Research Department Electronics and Telecommunications

ISBN: (纸本)9781424447749

This paper presents a novel approach for face detection, which is based on the discriminative MspLBP features selected by a boosting technique called the Ada-LDA method. By scanning the face image with a scalable sub-window, many sub-regions are obtained from which the MspLBP features are extracted to describe the local structures of a face image. From a large pool of the MspLBP features within the face image, the most discriminative MspLBP features that are trained by two alternative LDA methods depending on the singularity of the within-class scatter matrix of the training samples are selected under the framework of AdaBoost. To verify the feasibility of our face detector, we performed extensive experiments on the MIT-CBCL and MIT+CMU face test sets. Given the same number of features, the proposed face detector shows a detection rate of 25％ higher than the well-known Viola's detector at a given false positive rate of 10％. Challenging experimental results prove that our face detector can show promising detection performance with only a small number of the discriminative MspLBP features. It can also provide real-time performance. Our face detector can operate at over 16 frames per second.

关键词： Facial Recognition Face Face detector detection rate (DR) S-matrix theory LBP gene LBP multi-scale numerical invariant

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SOA-Enabled Health Information Integration Platform (HIIP): A Case Study

SOA-Enabled Health Information Integration Platform (HIIP): ...

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Fifth International Conference on Semantics,knowledge and Grid(第五届语义、知识与网格国际会议 SKG 2009)

作者： Haiyan Chen Jianxun Liu Shigang Qin Jian Cao Key Lab of Knowledge Processing and Networked Manufacture Hunan University of Science and Technolog Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

The research of health information integration is one of the hot topics in health information systems. Plenty of heterogeneous legacy systems exist in hospitals now due to many reasons. This leads to new problems that the communication among these systems is very difficult. It becomes a challenge for achieving a total-integrated health information system solution. To solve this problem, this paper proposes a health information integration platform based on Service- Oriented Architecture and Web services. An integrated client, which employs the data redirection techniques in operating systems and is called the universal healthinformation integration component, is developed. A real case study is used to show the design and implementation details as well as the valid integration among the heterogeneous system we have obtained.

关键词： Web Service Data Stream Redirection Information Integration

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Metadata as seeds for building an ontology driven information retrieval system

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International Journal of Hybrid Intelligent Systems 2009年第3期6卷 169-186页

作者： Zhuhadar, Leyla Nasraoui, Olfa Wyatt, Robert Romero, Elizabeth Knowledge Discovery and Web Mining Lab Department of Computer Engineering and Computer Science University of Louisville KY 40292 USA Office of Distance Learning Division of Extended Learning and Outreach Western Kentucky University KY 42101 USA

This paper presents an approach for an automated discovery, categorization and retrieval of metadata enriched E-learning resources. This research has further been implemented on a real platform “HyperManyMedia” at Western Kentucky University. It also presents the contribution that this work has made to the Adaptive Hypermedia systems. The main research question guiding this work is whether it is feasible and benecial to add the metadata to learning resources, while still being able to retrieve learning resources that are satisfactory and effective for the learner. The main goals of our HyperManyMedia system as implementation based on the suggested architecture, are to: (1) provide the learner with metadata search engine to overcome the limitations of searching for learning objects, and (2) be an open source repository for online learning.

关键词： knowledge engineering ontology semantic web information retrieval E-learning

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Generating the semantic containers for the query interfaces of deep web

Generating the semantic containers for the query interfaces ...

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International Conference on Management and Service science, MASS 2009

作者： Hao, Liang Wanli, Zuo Jian, Chen Yunge, Mao College of Computer Science and Technology Jilin University Changchun 130012 China Department of Information Changchun Taxation College Changchun 130117 China Key Laboratory of Symbol Computation Knowledge Engineering of the Ministry of Education Changchun 130012 China Network Center of Changchun Taxation College Changchun 130117 China

ISBN: (纸本)9781424446391

With the myriad emergence of the online Web Database, the Web is divided into a two layers information platform which is composed of Surface Web and Deep Web. The huge information hidden in the Deep Web is higher in the quality than the Surface Web. This interests the researchers of the traditional Database community. In order to adapt the Web community, the idea of information fusion is further transformed. However, the nature of the Web is great different from the Database in structure, principle and function. Query reformulation is one of the technical challenges. The only accessible method to get the information in the Deep Web is through the query interfaces provided by the Website of Deep Web. There are many semantic restrictions between the attributes in the query interface. Some attributes are co-occurred and the others are exclusive sometimes. To generate a valid query, we have to reconcile the key attributes and their semantic relations. To address the problem, a method based on the HTML codes is presented in this paper. Different kinds of semantic containers can be got through analyzing the codes of the query interface. The experiment is carried out on the famous Dataset of Deep Web to show the feasibility of the method. ©2009 IEEE.

关键词： Semantics

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Automated Discovery, Categorization and Retrieval of Personalized Semantically Enriched E-learning Resources

Automated Discovery, Categorization and Retrieval of Persona...

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International Conference on Semantic Computing

作者： Leyla Zhuhadar Olfa Nasraoui Robert Wyatt Elizabeth Romero Knowledge Discovery and Web Mining Lab Department of Computer Engineering and Computer Science University of Louisville Louisville KY USA Office of Distance Learning Western Kentucky University KY USA

ISBN: (纸本)9781424449620

In this paper, we describe an integrated and working E-learning search system for retrieving personalized semantically enriched learning resources. Within this context, this work proposes an architecture divided into four layers: (1) Semantic Representation (knowledge representation), (2) Algorithms, which are the core engine of this study, (3) Personalization Interface to deal with information filtering, and (4) Dual representation of the semantic user profile. We use Cluster Analysis in support of an adaptive personalized search for E-learning. This work ends with an experimental evaluation of the results and an overview of future research. Evidence is found that both personalization and semantic enrichment are potential elements for improving an E-learning Information Retrieval System.

关键词： Electronic learning Information filtering Information retrieval USA Councils knowledge representation Filtering algorithms Engines Machine learning algorithms Web mining knowledge engineering

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Towards semantic tagging in collaborative environments

Towards semantic tagging in collaborative environments

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International Conference on Digital Signal Processing (DSP)

作者： K. Chandramouli T. Kliegr V. Svatek E. Izquierdo School of Electronic Engineering and Computer Science Queen Mary University of London UK Department of Information and Knowledge Engineering Faculty of Informatics and Statistics University of Economics Prague Czech Republic

Tags pose an efficient and effective way of organization of resources, but they are not always available. A technique called SCM/THD investigated in this paper extracts entities from free-text annotations, and using the Lin similarity measure over the WordNet thesaurus classifies them into a controlled vocabulary of tags. Hypernyms extracted from Wikipedia are used to map uncommon entities to Wordnet synsets. In collaborative environments, users can assign multiple annotations to the same object hence increasing the amount of information available. Assuming that the semantics of the annotations overlap, this redundancy can be exploited to generate higher quality tags. A preliminary experiment presented in the paper evaluates the consistency and quality of tags generated from multiple annotations of the same image. The results obtained on an experimental dataset comprising of 62 annotations from four annotators show that the accuracy of a simple majority vote surpasses the average accuracy obtained through assessing the annotations individually by 18%. A moderate-strength correlation has been found between the quality of generated tags and the consistency of annotations.

关键词： Tagging Collaboration Collaborative work knowledge engineering Wikipedia Taxonomy Ontologies computer science Informatics Statistics

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Reports of the AAAI 2009 spring symposia

Reports of the AAAI 2009 spring symposia

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作者： Bao, Jie Bojars, Uldis Choudhury, Tanzeem Ding, Li Greaves, Mark Kapoor, Ashish Louchart, Sandy Mehta, Manish Nebel, Bernhard Nirenburg, Sergei Oates, Tim Roberts, David L. Sanfilippo, Antonio Stojanovic, Nenad Stubbs, Kristen Thomaz, Andrea L. Tsui, Katherine Woelfl, Stefan Tetherless World Constellation Rensselaer Polytechnic Institute United States Social Software Unit of DERI Galway Ireland Computer Science Department Dartmouth College United States Knowledge Systems at Vulcan Inc United States Adaptive Systems and Interaction Group Microsoft Research Redmond United States School for Mathematics and Computer Sciences Heriot-Watt University United Kingdom School ot Interactive Computing Georgia Institute of Technology United States Department of Computer Science University of Freiburg Germany Computer Science and Electrical Engineering Department University of Maryland Baltimore County United States Pacific Northwest National Laboratory Richland WA United States University of Karlsruhe Germany IRobot Corporation United States University of Massachusetts Lowell United States

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's department of computer science, was pleased to present the 2009 Spring Symposium Series, held Monday through Wednesday, March 23-25, 2009, at Stanford University. The titles of the nine symposia were Agents That Learn from Human Teachers, Benchmarking of Qualitative Spatial and Temporal Reasoning Systems, Experimental Design for Real- World Systems, Human Behavior Modeling, Intelligent Event Processing, Intelligent Narrative Technologies II, Learning by Reading and Learning to Read, Social Semantic Web: Where Web 2.0 Meets Web 3.0, and Technosocial Predictive Analytics. The goal of the Agents That Learn from Human Teachers symposium was to investigate how we can enable software and robotics agents to leam from real-time interaction with an everyday human partner. The aim of the Benchmarking of Qualitative Spatial and Temporal Reasoning Systems symposium was to initiate the development of a problem repository in the field of qualitative spatial and temporal reasoning and identify a graded set of challenges for future midterm and long-term research. The Experimental Design symposium discussed the challenges of evaluating AI systems. The Human Behavior Modeling symposium explored reasoning methods for understanding various aspects of human behavior, especially in the context of designing intelligent systems that interact with humans. The Intelligent Event Processing symposium discussed the need for more Al-based approaches in event pro-cessing and defined a kind of research agenda for the field, coined as intelligent complex event processing (iCEP). The Intelligent Narrative Technologies IIAAAI symposium discussed innovations, progress, and novel techniques in the research domain. The Learning by Reading and Learning to Read symposium explored two aspects of making natural language texts semantically accessible to, and processable by, machines. The Social Semantic

关键词： Benchmarking

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