Supporting learners in inclusive lifelong learning scenarios requires a dynamic support that takes into account their learning needs and preferences. This research is focused on an open standard-based recommender system, covering the full life cycle of eLearning. The recommending system I am developing is supported by a multi-agent architecture and its ultimate goal is to improve the learning efficiency and the learnerspsila satisfaction during the execution of the course tasks.
{"title":"Recommending in Inclusive Lifelong Learning Scenarios: Identifying and Managing Runtime Situations","authors":"O. Santos","doi":"10.1109/WIIAT.2008.251","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.251","url":null,"abstract":"Supporting learners in inclusive lifelong learning scenarios requires a dynamic support that takes into account their learning needs and preferences. This research is focused on an open standard-based recommender system, covering the full life cycle of eLearning. The recommending system I am developing is supported by a multi-agent architecture and its ultimate goal is to improve the learning efficiency and the learnerspsila satisfaction during the execution of the course tasks.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121895573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
One of the cornerstones of the Social Web is informal user-generated metadata (or tags) for annotating web objects like pages, images, and videos. However, many real-world domains are currently left out of the social tagging phenomenon due to the lack of a wide-scale tagging-savvy audience - domains like the personal desktop, enterprise intranets, and digital libraries. Hence in this paper, we propose a lightweight interactive tagging framework for providing high-quality tag suggestions for the vast majority of untagged content. One of the salient features of the proposed framework is its incorporation of user feedback for iteratively refining tag suggestions. Concretely, we describe and evaluate three feedback models - Tag-Based, Term-Based, and Tag Co-location. Through extensive user evaluation and testing, we find that feedback can significantly improve tag quality with minimal user involvement.
{"title":"Exploring Feedback Models in Interactive Tagging","authors":"R. Graham, James Caverlee","doi":"10.1109/WIIAT.2008.419","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.419","url":null,"abstract":"One of the cornerstones of the Social Web is informal user-generated metadata (or tags) for annotating web objects like pages, images, and videos. However, many real-world domains are currently left out of the social tagging phenomenon due to the lack of a wide-scale tagging-savvy audience - domains like the personal desktop, enterprise intranets, and digital libraries. Hence in this paper, we propose a lightweight interactive tagging framework for providing high-quality tag suggestions for the vast majority of untagged content. One of the salient features of the proposed framework is its incorporation of user feedback for iteratively refining tag suggestions. Concretely, we describe and evaluate three feedback models - Tag-Based, Term-Based, and Tag Co-location. Through extensive user evaluation and testing, we find that feedback can significantly improve tag quality with minimal user involvement.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"67 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125962922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Much early evaluation work focused specifically on the "accuracy" of recommendation algorithms. Good recommendation (in terms of accuracy) has, however, to be coupled with other considerations. This work suggests measures aiming at evaluating other aspects than accuracy of recommendation algorithms. Other considerations include (1) coverage, which measures the percentage of a data set that a recommender system is able to provide recommendation for, (2) confidence metrics that can help users make more effective decisions, (3) computing time, which measures how quickly an algorithm can produce good recommendations, (4) novelty/serendipity, which measure whether a recommendation is original, and (5) robustness which measure the ability of the algorithm to make good predictions in the presence of noisy or sparse data. Six collaborative recommendation methods are investigated. Results on artificial data sets (for robustness) or on the real MovieLens data set (for accuracy, novelty, and computing time) are included and analyzed, showing that kernel-based algorithms provide the best results overall.
{"title":"Evaluating Performance of Recommender Systems: An Experimental Comparison","authors":"François Fouss, M. Saerens","doi":"10.1109/WIIAT.2008.252","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.252","url":null,"abstract":"Much early evaluation work focused specifically on the \"accuracy\" of recommendation algorithms. Good recommendation (in terms of accuracy) has, however, to be coupled with other considerations. This work suggests measures aiming at evaluating other aspects than accuracy of recommendation algorithms. Other considerations include (1) coverage, which measures the percentage of a data set that a recommender system is able to provide recommendation for, (2) confidence metrics that can help users make more effective decisions, (3) computing time, which measures how quickly an algorithm can produce good recommendations, (4) novelty/serendipity, which measure whether a recommendation is original, and (5) robustness which measure the ability of the algorithm to make good predictions in the presence of noisy or sparse data. Six collaborative recommendation methods are investigated. Results on artificial data sets (for robustness) or on the real MovieLens data set (for accuracy, novelty, and computing time) are included and analyzed, showing that kernel-based algorithms provide the best results overall.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124676977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper addresses practical aspects of Web page classification not captured by the classical text mining framework. Classifiers are supposed to perform well on a broad variety of pages. We argue that constructing training corpora is a bottleneck for building such classifiers, and that care has to be taken if the goal is to generalize to previously unseen kinds of pages on the Web. We study techniques for building training corpora automatically from publicly available Web resources, quantify the discrepancy between them, and demonstrate that encouraging agreement between classifiers given such diverse sources drastically outperforms methods that ignore the different natures of data sources on the Web.
{"title":"Leveraging Web 2.0 Sources for Web Content Classification","authors":"Somnath Banerjee, Martin Scholz","doi":"10.1109/WIIAT.2008.291","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.291","url":null,"abstract":"This paper addresses practical aspects of Web page classification not captured by the classical text mining framework. Classifiers are supposed to perform well on a broad variety of pages. We argue that constructing training corpora is a bottleneck for building such classifiers, and that care has to be taken if the goal is to generalize to previously unseen kinds of pages on the Web. We study techniques for building training corpora automatically from publicly available Web resources, quantify the discrepancy between them, and demonstrate that encouraging agreement between classifiers given such diverse sources drastically outperforms methods that ignore the different natures of data sources on the Web.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124768325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we are looking for a relationship between the intent of Web pages, their architecture and the communities who take part in their usage and creation. For us, the Web page is entity carrying information about these communities. Our paper describes techniques, which can be used to extract mentioned information as well as tools usable in analysis of these information. Information about communities could be used in several ways thanks to our approach. Finally we present an experiment which proves the feasibility of our approach.
{"title":"Web Communities Defined by Web Page Content","authors":"M. Kudelka, V. Snás̃el, Z. Horak, A. Hassanien","doi":"10.1109/WIIAT.2008.93","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.93","url":null,"abstract":"In this paper we are looking for a relationship between the intent of Web pages, their architecture and the communities who take part in their usage and creation. For us, the Web page is entity carrying information about these communities. Our paper describes techniques, which can be used to extract mentioned information as well as tools usable in analysis of these information. Information about communities could be used in several ways thanks to our approach. Finally we present an experiment which proves the feasibility of our approach.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129747702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The World Wide Web contains wide variety of news reports, arguments, opinions, etc. that vary widely in quality. People judge the credibility of information on the Web for decision making in daily life. At present, while the quantity of information on the Web is explosively increasing, it is necessary to develop a system that supports such judgments. We have been developing an information credibility analysis system, WISDOM that considers the viewpoints of information contents, information senders, and information appearances. In this paper, as a viewpoint of information contents, we propose a method for providing a bird's eye view of major statements on a given topic and their contradictions. We evaluate the obtained statements in our experiments, and confirm the effectiveness of our approach. Furthermore, we discuss our future objectives.
{"title":"Grasping Major Statements and Their Contradictions Toward Information Credibility Analysis of Web Contents","authors":"Daisuke Kawahara, S. Kurohashi, Kentaro Inui","doi":"10.1109/WIIAT.2008.289","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.289","url":null,"abstract":"The World Wide Web contains wide variety of news reports, arguments, opinions, etc. that vary widely in quality. People judge the credibility of information on the Web for decision making in daily life. At present, while the quantity of information on the Web is explosively increasing, it is necessary to develop a system that supports such judgments. We have been developing an information credibility analysis system, WISDOM that considers the viewpoints of information contents, information senders, and information appearances. In this paper, as a viewpoint of information contents, we propose a method for providing a bird's eye view of major statements on a given topic and their contradictions. We evaluate the obtained statements in our experiments, and confirm the effectiveness of our approach. Furthermore, we discuss our future objectives.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128351502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We analyse data obtained from several collaborative tagging systems and discover that user interests can be very diverse. Traditional methods for representing interests of users are usually not able to reflect such diversity. We propose a method to construct user profiles of multiple interests using data in a collaborative tagging system. Our evaluation suggests that the proposed method is able to generate user profiles which reflect the diversity of user interests and can be used to help provide more focused recommendation.
{"title":"Discovering and Modelling Multiple Interests of Users in Collaborative Tagging Systems","authors":"C. Yeung, Nicholas Gibbins, N. Shadbolt","doi":"10.1109/WIIAT.2008.267","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.267","url":null,"abstract":"We analyse data obtained from several collaborative tagging systems and discover that user interests can be very diverse. Traditional methods for representing interests of users are usually not able to reflect such diversity. We propose a method to construct user profiles of multiple interests using data in a collaborative tagging system. Our evaluation suggests that the proposed method is able to generate user profiles which reflect the diversity of user interests and can be used to help provide more focused recommendation.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"290 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128458279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the current information age, peoplepsilas lives are driven by the availability and utilization of services to get information anytime, anywhere, in any format, and on any device. For a nomadic user, information becomes useful if certain scales of autonomy and intelligence are present in the information systems. In this context lightweight multi agent systems (L-MAS) become a preferable choice for design and development of intelligent autonomous mobile information systems. In this paper we aim to propose a multi agent based system architecture to bring OWL based semantic Web services to nomadic users. We propose a design for smart nomadic client using, L-MAS, which interacts with a multi agent based mediator system to get access to the OWL based semantic Web services.
{"title":"Service Interoperability between Agents and Semantic Web Services for Nomadic Environment","authors":"Adeel Shajjar, N. Khalid, H. F. Ahmad, H. Suguri","doi":"10.1109/WIIAT.2008.327","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.327","url":null,"abstract":"In the current information age, peoplepsilas lives are driven by the availability and utilization of services to get information anytime, anywhere, in any format, and on any device. For a nomadic user, information becomes useful if certain scales of autonomy and intelligence are present in the information systems. In this context lightweight multi agent systems (L-MAS) become a preferable choice for design and development of intelligent autonomous mobile information systems. In this paper we aim to propose a multi agent based system architecture to bring OWL based semantic Web services to nomadic users. We propose a design for smart nomadic client using, L-MAS, which interacts with a multi agent based mediator system to get access to the OWL based semantic Web services.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128466484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Liu, Jia Yue, Xiaoyu Wang, A. Raja, W. Ribarsky
Knowledge gathering and investigative tasks in open environments can be very complex because the problem-solving context is constantly evolving, and the data may be incomplete, unreliable and/or conflicting. This paper significantly extends our previous work on a mixed-initiative agent by making it capable of assisting humans in foraging task analysis using AI blackboard-based reasoning, visualizations and a mix-initiative user interface. The agent is equipped with the ability to adapt its processing to available resources, deadlines and its current problem-solving context.
{"title":"The Role of Blackboard-Based Reasoning and Visual Analytics in RESIN's Predictive Analysis","authors":"D. Liu, Jia Yue, Xiaoyu Wang, A. Raja, W. Ribarsky","doi":"10.1109/WIIAT.2008.307","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.307","url":null,"abstract":"Knowledge gathering and investigative tasks in open environments can be very complex because the problem-solving context is constantly evolving, and the data may be incomplete, unreliable and/or conflicting. This paper significantly extends our previous work on a mixed-initiative agent by making it capable of assisting humans in foraging task analysis using AI blackboard-based reasoning, visualizations and a mix-initiative user interface. The agent is equipped with the ability to adapt its processing to available resources, deadlines and its current problem-solving context.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129803792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
From an external perspective, cognitive agent behaviour can be described by specifying (temporal) correlations of a certain complexity between stimuli (input states) and (re)actions (output states) of the agent. From an internal perspective the agentpsilas dynamics can be characterized by direct (causal) temporal relations between internal cognitive states of the agent. Internal dynamics and externally observable behaviour of an agent have reciprocal relations with each other. This paper contributes an approach that allows automatic generation of a behavioural specification of an agent from a cognitive process model. Furthermore, by this automated transformation, internal cognitive state properties of an agent can be related by a representation relation to externally observable behavioural patterns.
{"title":"Relating Cognitive Process Models to Behavioural Models of Agents","authors":"A. Sharpanskykh, Jan Treur","doi":"10.1109/WIIAT.2008.246","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.246","url":null,"abstract":"From an external perspective, cognitive agent behaviour can be described by specifying (temporal) correlations of a certain complexity between stimuli (input states) and (re)actions (output states) of the agent. From an internal perspective the agentpsilas dynamics can be characterized by direct (causal) temporal relations between internal cognitive states of the agent. Internal dynamics and externally observable behaviour of an agent have reciprocal relations with each other. This paper contributes an approach that allows automatic generation of a behavioural specification of an agent from a cognitive process model. Furthermore, by this automated transformation, internal cognitive state properties of an agent can be related by a representation relation to externally observable behavioural patterns.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127153952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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