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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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}
The task of outlier identification is to find small groups of data objects that are exceptional when compared with rest large amount of data. The identification of outliers can lead to the discovery of truly unexpected knowledge in areas such as electronic commerce, credit card frauds, voting irregularity analysis, data cleansing, network intrusion, severe weather prediction & many more. This paper deals with the identification of outliers and to get efficient clusters in fuzzy clustering. In this paper a new density based definition of outlier and an algorithm dasiaDFCMpsila is proposed; which works in two phases. In first phase, it identifies outliers and separate them from original data-set and in the second phase, it creates clusters from noiseless data. DFCM modifies FCM fuzzy clustering technique to create clusters. But it can also be implemented with any other fuzzy clustering technique. Numerical examples and tests show that proposed algorithm gives better result when compared with FCM.
{"title":"DFCM: Density Based Approach to Identify Outliers and to Get Efficient Clusters in Fuzzy Clustering","authors":"Prabhjot Kaur","doi":"10.1109/WIIAT.2008.58","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.58","url":null,"abstract":"The task of outlier identification is to find small groups of data objects that are exceptional when compared with rest large amount of data. The identification of outliers can lead to the discovery of truly unexpected knowledge in areas such as electronic commerce, credit card frauds, voting irregularity analysis, data cleansing, network intrusion, severe weather prediction & many more. This paper deals with the identification of outliers and to get efficient clusters in fuzzy clustering. In this paper a new density based definition of outlier and an algorithm dasiaDFCMpsila is proposed; which works in two phases. In first phase, it identifies outliers and separate them from original data-set and in the second phase, it creates clusters from noiseless data. DFCM modifies FCM fuzzy clustering technique to create clusters. But it can also be implemented with any other fuzzy clustering technique. Numerical examples and tests show that proposed algorithm gives better result when compared with FCM.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122354443","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 model the sum and product riddle in public announcement logic, which is interpreted on an epistemic Kripke model. The model is symbolically represented as a finite state program with n agents. A model checking method to the riddle is developed by using the BDD-based symbolic model checking algorithm for logic of knowledge we developed in [7]. The method is implemented by extending the model checker MCTK [7] and then the solution of the riddle is verified successfully.
{"title":"Solving Sum and Product Riddle via BDD-Based Model Checking","authors":"Xiangyu Luo, Kaile Su, A. Sattar, Yan Chen","doi":"10.1109/WIIAT.2008.277","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.277","url":null,"abstract":"We model the sum and product riddle in public announcement logic, which is interpreted on an epistemic Kripke model. The model is symbolically represented as a finite state program with n agents. A model checking method to the riddle is developed by using the BDD-based symbolic model checking algorithm for logic of knowledge we developed in [7]. The method is implemented by extending the model checker MCTK [7] and then the solution of the riddle is verified successfully.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132495058","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 investigate the following data mining problems from the document retrieval: From a large data set of documents, we need to find documents that relate to human interest as few iterations of human testing or checking as possible. In each iteration a comparatively small batch of documents is evaluated for relating to the human interest. We apply active learning techniques based on Support Vector Machine for evaluating successive batches, which is called relevance feedback. Our proposed approach has been very useful for document retrieval with relevance feedback experimentally. In this paper, we adopt several Vector Space Models into our proposed method, and then show the comparison results of the performance of our method in several Vector Space Models.
{"title":"Comparison of Performance for SVM Based Relevance Feedback Document Retrieval in Several Vector Space Models","authors":"T. Onoda, H. Murata, S. Yamada","doi":"10.1109/WIIAT.2008.101","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.101","url":null,"abstract":"We investigate the following data mining problems from the document retrieval: From a large data set of documents, we need to find documents that relate to human interest as few iterations of human testing or checking as possible. In each iteration a comparatively small batch of documents is evaluated for relating to the human interest. We apply active learning techniques based on Support Vector Machine for evaluating successive batches, which is called relevance feedback. Our proposed approach has been very useful for document retrieval with relevance feedback experimentally. In this paper, we adopt several Vector Space Models into our proposed method, and then show the comparison results of the performance of our method in several Vector Space Models.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130917471","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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