J. Blee, D. Billington, Guido Governatori, A. Sattar
The use of rational agents for modelling real world problems has both been heavily investigated and become well accepted, with BDI Logic being a widely used architecture to represent and reason about rational agency. However, in the real world, we often have to deal with different levels of confidence in our beliefs, desires, and intentions. This paper extends our previous framework that integrated qualitative levels into BDI logic. We describe an expanded set of axioms and properties of the extended logic and also define a detailed non-normal Kripke type semantics.
{"title":"Levels of Modalities for BDI Logic","authors":"J. Blee, D. Billington, Guido Governatori, A. Sattar","doi":"10.1109/WIIAT.2008.231","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.231","url":null,"abstract":"The use of rational agents for modelling real world problems has both been heavily investigated and become well accepted, with BDI Logic being a widely used architecture to represent and reason about rational agency. However, in the real world, we often have to deal with different levels of confidence in our beliefs, desires, and intentions. This paper extends our previous framework that integrated qualitative levels into BDI logic. We describe an expanded set of axioms and properties of the extended logic and also define a detailed non-normal Kripke type semantics.","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":"124282854","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}
Specification and verification of access control (AC) policies is a significant and challenging problem. Colored Petri net (CPN) is a powerful modeling and analyzing tool having the advantages of intuitive visual framework with the rigor and precision of a semantics founded on category theory. In this paper, a concrete specification of SA-RBAC policy on CPN is described in detail for our improved RBAC model SA-RBAC (self-authentication RBAC). And all the states in the CPN model describing SA-RBAC policy can be proved to be consistent.
{"title":"Specification of SA-RBAC Policy Based on Colored Petri Net","authors":"Mingqiu Song, Zhiguo Pang","doi":"10.1109/WIIAT.2008.189","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.189","url":null,"abstract":"Specification and verification of access control (AC) policies is a significant and challenging problem. Colored Petri net (CPN) is a powerful modeling and analyzing tool having the advantages of intuitive visual framework with the rigor and precision of a semantics founded on category theory. In this paper, a concrete specification of SA-RBAC policy on CPN is described in detail for our improved RBAC model SA-RBAC (self-authentication RBAC). And all the states in the CPN model describing SA-RBAC policy can be proved to be consistent.","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":"125198952","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}
Confronting the challenges of annotating naturally occurring text into a semantically structured form to facilitate automatic information extraction, current semantic role labeling (SRL) systems have been specifically examining a semantic predicate-argument structure. Based on the concept description language for natural language (CDL.nl) which is intended to describe the concept structure of text using a set of pre-defined semantic relations, we develop a parser to add a new layer of semantic annotation of natural language sentences as an extension of SRL. With the assumption that all relation instances are detected, we present a relation classification approach facing the challenges of CDL.nl relation extraction. Preliminary evaluation on a manual dataset, using support vector machine, shows that CDL.nl relations can be classified with good performance.
{"title":"Relation Classification for Semantic Structure Annotation of Text","authors":"Yulan Yan, Y. Matsuo, M. Ishizuka, T. Yokoi","doi":"10.1109/WIIAT.2008.128","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.128","url":null,"abstract":"Confronting the challenges of annotating naturally occurring text into a semantically structured form to facilitate automatic information extraction, current semantic role labeling (SRL) systems have been specifically examining a semantic predicate-argument structure. Based on the concept description language for natural language (CDL.nl) which is intended to describe the concept structure of text using a set of pre-defined semantic relations, we develop a parser to add a new layer of semantic annotation of natural language sentences as an extension of SRL. With the assumption that all relation instances are detected, we present a relation classification approach facing the challenges of CDL.nl relation extraction. Preliminary evaluation on a manual dataset, using support vector machine, shows that CDL.nl relations can be classified with good performance.","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":"129247448","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}
Web users exhibit a variety of navigational interests through clicking a sequence of Web pages. Analysis of Web usage data will lead to discover Web user access pattern and facilitate users locate more preferable Web pages via collaborative recommending technique. Meanwhile, latent semantic analysis techniques provide a powerful means to capture user access pattern and associated task space. In this paper, we propose a collaborative Web recommendation framework, which employs Latent Dirichlet Allocation (LDA) to model underlying topic-simplex space and discover the associations between user sessions and multiple topics via probability inference. Experiments conducted on real Website usage dataset show that this approach can achieve better recommendation accuracy in comparison to existing techniques. The discovered topic-simplex expression can also provide a better interpretation of user navigational preference.
{"title":"Modelling User Behaviour for Web Recommendation Using LDA Model","authors":"Guandong Xu, Yanchun Zhang, X. Yi","doi":"10.1109/WIIAT.2008.313","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.313","url":null,"abstract":"Web users exhibit a variety of navigational interests through clicking a sequence of Web pages. Analysis of Web usage data will lead to discover Web user access pattern and facilitate users locate more preferable Web pages via collaborative recommending technique. Meanwhile, latent semantic analysis techniques provide a powerful means to capture user access pattern and associated task space. In this paper, we propose a collaborative Web recommendation framework, which employs Latent Dirichlet Allocation (LDA) to model underlying topic-simplex space and discover the associations between user sessions and multiple topics via probability inference. Experiments conducted on real Website usage dataset show that this approach can achieve better recommendation accuracy in comparison to existing techniques. The discovered topic-simplex expression can also provide a better interpretation of user navigational preference.","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":"129390718","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 propose a neural-network-based visualization system of geographic tendency. In general, there are some needs of understanding statistical data of geographic tendency, such as geographic marketing data, real-estate prices, and so on. The main purpose of the proposal is to visualize the tendency of these data online with interactive mapping systems, such as Google Maps. The proposed system generates translucent images of a heatmap, which shows the geographic tendency like thermograph. It consists of two steps: (1) construction of a tendency model with a neural network, (2) determine the color scale for the output heatmap. As for (1), a general regression neural network (GRNN) is employed to compose a tendency model by function approximation. As for (2), the output color scale is optimized and the heatmap is finally generated using the composed tendency model.
{"title":"A Neural-Network-Based Geographic Tendency Visualization","authors":"Hajime Hotta, M. Hagiwara","doi":"10.1109/WIIAT.2008.141","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.141","url":null,"abstract":"In this paper, we propose a neural-network-based visualization system of geographic tendency. In general, there are some needs of understanding statistical data of geographic tendency, such as geographic marketing data, real-estate prices, and so on. The main purpose of the proposal is to visualize the tendency of these data online with interactive mapping systems, such as Google Maps. The proposed system generates translucent images of a heatmap, which shows the geographic tendency like thermograph. It consists of two steps: (1) construction of a tendency model with a neural network, (2) determine the color scale for the output heatmap. As for (1), a general regression neural network (GRNN) is employed to compose a tendency model by function approximation. As for (2), the output color scale is optimized and the heatmap is finally generated using the composed tendency model.","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":"129558684","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 aim of this contribution is to present the work that the Universidad Industrial de Santander (UIS) is currently carrying out through the institutional project named ProSPETIC, designed to give support to academic programs using ICTs. The development is based on principles of the instructional engineering considering methods for the design, development and planning of the learning systems distribution that integrate concepts, processes and principles of instructional design, cognitive modeling and software engineering. Learning objects that support the initiatives are structured under SCORM guidelines and they are used to assist face to face and distance education activities through a virtual learning environment built as an adaptive hypermedia multiagent system.
{"title":"Competence Formation through Learning Objects in a Multiagent Virtual Educational Environment","authors":"C. Peña, S. Gómez, C. Mejía, R. Fabregat","doi":"10.1109/WIIAT.2008.400","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.400","url":null,"abstract":"The aim of this contribution is to present the work that the Universidad Industrial de Santander (UIS) is currently carrying out through the institutional project named ProSPETIC, designed to give support to academic programs using ICTs. The development is based on principles of the instructional engineering considering methods for the design, development and planning of the learning systems distribution that integrate concepts, processes and principles of instructional design, cognitive modeling and software engineering. Learning objects that support the initiatives are structured under SCORM guidelines and they are used to assist face to face and distance education activities through a virtual learning environment built as an adaptive hypermedia multiagent system.","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":"129600412","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}
E. Papadopoulou, S. McBurney, N. Taylor, M. H. Williams
Two important concepts in developing ubiquitous or pervasive computing technologies that are acceptable to the end user are personalization and privacy. On the one hand it is essential to take account of user needs and preferences to personalize decision making within such a system, on the other hand it is equally important to protect user privacy. One approach to handling user privacy is through the use of virtual identities. This has the advantage that it can also benefit the handling of user preferences. In particular, virtual identities can be used as a substitute for roles. On the other hand user preferences can be used in identity management to assist in selecting a virtual identity to hide the real identity of the user, thereby improving user-friendliness of the system. This paper describes this symbiosis and how it is implemented in the Daidalos pervasive system.
{"title":"Linking Privacy and User Preferences in the Identity Management for a Pervasive System","authors":"E. Papadopoulou, S. McBurney, N. Taylor, M. H. Williams","doi":"10.1109/WIIAT.2008.331","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.331","url":null,"abstract":"Two important concepts in developing ubiquitous or pervasive computing technologies that are acceptable to the end user are personalization and privacy. On the one hand it is essential to take account of user needs and preferences to personalize decision making within such a system, on the other hand it is equally important to protect user privacy. One approach to handling user privacy is through the use of virtual identities. This has the advantage that it can also benefit the handling of user preferences. In particular, virtual identities can be used as a substitute for roles. On the other hand user preferences can be used in identity management to assist in selecting a virtual identity to hide the real identity of the user, thereby improving user-friendliness of the system. This paper describes this symbiosis and how it is implemented in the Daidalos pervasive system.","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":"130900868","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}
Collaborative filtering recommender systems make predictions based on the preferences of users considered like-minded to the target user (user-based), or the popularities of items similar to the target item (item-based). There have been several approaches of combining user-based and item-based collaborative filtering. However, they are predominantly along the lines of averaging user-based and item-based predictions in a close-to-linear fashion, thus behave like smoothing mechanisms and only work well on sparse datasets. This article proposes a new way of combining user and item based collaborative filtering in a nonlinear fashion. The goal of the approach is to improve recommendation accuracy on regular datasets, by means of a more sensible neighbourhood similarity computation method that guides the user similarity computation using the itemspsila similarities to the item that is being predicted.
{"title":"Iterative Neighbourhood Similarity Computation for Collaborative Filtering","authors":"Yun Zhang, Peter M. Andreae","doi":"10.1109/WIIAT.2008.222","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.222","url":null,"abstract":"Collaborative filtering recommender systems make predictions based on the preferences of users considered like-minded to the target user (user-based), or the popularities of items similar to the target item (item-based). There have been several approaches of combining user-based and item-based collaborative filtering. However, they are predominantly along the lines of averaging user-based and item-based predictions in a close-to-linear fashion, thus behave like smoothing mechanisms and only work well on sparse datasets. This article proposes a new way of combining user and item based collaborative filtering in a nonlinear fashion. The goal of the approach is to improve recommendation accuracy on regular datasets, by means of a more sensible neighbourhood similarity computation method that guides the user similarity computation using the itemspsila similarities to the item that is being predicted.","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":"128841622","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}
A Wiki is a collaborative Web page authoring system. Users collaborate to build a Web site by creating and updating Wiki pages through Web browsers. However, conventional Wikis easily lose the consistency of the contents because a number of anonymous users can participate in authoring them. By introducing information agents that understand the. Wiki contents, we can keep the consistency. The agents can automatically update Wiki contents, integrate other Web contents to them, and keep them consistent cooperating with the human users. We propose KawaWiki, which is a semantic Wiki system where human users and information agents can collaborate by utilizing the semantic Web technology. To make agents and users collaborate in authoring Wiki contents, we adopt the RDF as the common representation. It is not easy for novice users to author RDF data, and we introduce KawaWiki templates to generate a Wiki page with RDF data at one time. We also introduce KawaWiki queries to make agents retrieve information efficiently from the Wiki contents. Finally, we introduce an agent description language to specify agent's behavior on the Wiki.
{"title":"Semantic Wiki Where Human and Agents Collaborate","authors":"K. Kawamoto, M. Mase, Y. Kitamura, Y. Tijerino","doi":"10.1109/WIIAT.2008.240","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.240","url":null,"abstract":"A Wiki is a collaborative Web page authoring system. Users collaborate to build a Web site by creating and updating Wiki pages through Web browsers. However, conventional Wikis easily lose the consistency of the contents because a number of anonymous users can participate in authoring them. By introducing information agents that understand the. Wiki contents, we can keep the consistency. The agents can automatically update Wiki contents, integrate other Web contents to them, and keep them consistent cooperating with the human users. We propose KawaWiki, which is a semantic Wiki system where human users and information agents can collaborate by utilizing the semantic Web technology. To make agents and users collaborate in authoring Wiki contents, we adopt the RDF as the common representation. It is not easy for novice users to author RDF data, and we introduce KawaWiki templates to generate a Wiki page with RDF data at one time. We also introduce KawaWiki queries to make agents retrieve information efficiently from the Wiki contents. Finally, we introduce an agent description language to specify agent's behavior on the Wiki.","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":"128910846","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}
Agent decision-making is an information-intensive activity. Its performance is affected by the availability of relevant information. Bayesian networks have provided a probabilistic estimate for uncertain information. However, for those decision problems where information is represented in predicates, Bayesian inferences are required to process the variable-bound relations across predicates. multi-layer Bayesian network (MLBN) is an extension of the classical model of Bayesian networks with multiple layers of conditional probability tables, each corresponding to one specific variable binding. The MLBN has been implemented based on an agent architecture. Experiments have shown its capability of improving performance in an experience-based decision-making framework.
{"title":"Multi-layer Bayesian Network for Variable-Bound Inference","authors":"Shizhuo Zhu, Po-Chun Chen, J. Yen","doi":"10.1109/WIIAT.2008.306","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.306","url":null,"abstract":"Agent decision-making is an information-intensive activity. Its performance is affected by the availability of relevant information. Bayesian networks have provided a probabilistic estimate for uncertain information. However, for those decision problems where information is represented in predicates, Bayesian inferences are required to process the variable-bound relations across predicates. multi-layer Bayesian network (MLBN) is an extension of the classical model of Bayesian networks with multiple layers of conditional probability tables, each corresponding to one specific variable binding. The MLBN has been implemented based on an agent architecture. Experiments have shown its capability of improving performance in an experience-based decision-making framework.","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":"122934765","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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