T. Bosse, C. Gerritsen, M. Hoogendoorn, S. W. Jaffry, Jan Treur
Within criminology, the process of crime displacement is usually explained by referring to the interaction of three types of agents: criminals, passers-by, and guardians. Most existing simulation models of this process are agent-based. However, when the number of agents considered becomes large, population-based simulation has computational advantages over agent-based simulation. This paper presents both an agent-based and a population-based simulation model of crime displacement, and reports a comparative evaluation of the two models. In addition, an approach is put forward to analyse the behaviour of both models by means of formal techniques.
{"title":"Comparison of Agent-Based and Population-Based Simulations of Displacement of Crime","authors":"T. Bosse, C. Gerritsen, M. Hoogendoorn, S. W. Jaffry, Jan Treur","doi":"10.1109/WIIAT.2008.333","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.333","url":null,"abstract":"Within criminology, the process of crime displacement is usually explained by referring to the interaction of three types of agents: criminals, passers-by, and guardians. Most existing simulation models of this process are agent-based. However, when the number of agents considered becomes large, population-based simulation has computational advantages over agent-based simulation. This paper presents both an agent-based and a population-based simulation model of crime displacement, and reports a comparative evaluation of the two models. In addition, an approach is put forward to analyse the behaviour of both models by means of formal techniques.","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":"128022328","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}
Shin-ya Sato, K. Fukuda, Toshio Hirotsu, S. Kurihara, T. Sugawara
We studied the problem of finding a subspace of Web pages that is contextually consistent for co-occurrence analysis. We looked at blogs and proposed blogger-based co-occurrence analysis, which assumes that two items are relevant to each other if they appear in any of the blog entries posted by the same blogger. We show that (1) blogger-based analysis outperforms conventional page-based analysis in solving context-sensitive problems and that (2) analysis focused on bloggers forming a community yields better performance compared with that focused on isolated bloggers.
{"title":"Co-occurrence Analysis Focused on Blogger Communities","authors":"Shin-ya Sato, K. Fukuda, Toshio Hirotsu, S. Kurihara, T. Sugawara","doi":"10.1109/WIIAT.2008.28","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.28","url":null,"abstract":"We studied the problem of finding a subspace of Web pages that is contextually consistent for co-occurrence analysis. We looked at blogs and proposed blogger-based co-occurrence analysis, which assumes that two items are relevant to each other if they appear in any of the blog entries posted by the same blogger. We show that (1) blogger-based analysis outperforms conventional page-based analysis in solving context-sensitive problems and that (2) analysis focused on bloggers forming a community yields better performance compared with that focused on isolated bloggers.","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":"125963023","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. Santos, Hien Nguyen, Fei Yu, K. Kim, Deqing Li, J. T. Wilkinson, Adam Olson, Russell Jacob
When decisions need to be made in government, the intelligence community (IC) is tasked with analyzing the situation. This analysis is based on a huge amount of information and usually under severe time constraints. As such, it is particularly vulnerable to attacks from insiders with malicious intent. A malicious insider may alter, fabricate, or hide critical information in their analytical products, such as reports, in order to interfere with the decision making process. In this paper, we focus on detecting such malicious insiders. Malicious actions such as disinformation tend to be very subtle and thus difficult to detect. Therefore, we employ a user modeling technique to model an insider based on logged information and documents accessed while accomplishing an intelligence analysis task. We create a computational model for each insider and apply several detection metrics to analyze this model as it changes over time. If any deviation of behavior is detected, alerts can be issued. A pilot test revealed that the computed deviations had a high correlation with insiderspsila cognitive styles. Based on this finding, we designed a framework that minimized the impact of differences in cognitive styles. In our evaluation, we used data collected from intelligence analysts, and simulated malicious insiders based on this data. A high percentage of the simulated malicious insiders were successfully detected.
{"title":"Intent-Driven Insider Threat Detection in Intelligence Analyses","authors":"E. Santos, Hien Nguyen, Fei Yu, K. Kim, Deqing Li, J. T. Wilkinson, Adam Olson, Russell Jacob","doi":"10.1109/WIIAT.2008.376","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.376","url":null,"abstract":"When decisions need to be made in government, the intelligence community (IC) is tasked with analyzing the situation. This analysis is based on a huge amount of information and usually under severe time constraints. As such, it is particularly vulnerable to attacks from insiders with malicious intent. A malicious insider may alter, fabricate, or hide critical information in their analytical products, such as reports, in order to interfere with the decision making process. In this paper, we focus on detecting such malicious insiders. Malicious actions such as disinformation tend to be very subtle and thus difficult to detect. Therefore, we employ a user modeling technique to model an insider based on logged information and documents accessed while accomplishing an intelligence analysis task. We create a computational model for each insider and apply several detection metrics to analyze this model as it changes over time. If any deviation of behavior is detected, alerts can be issued. A pilot test revealed that the computed deviations had a high correlation with insiderspsila cognitive styles. Based on this finding, we designed a framework that minimized the impact of differences in cognitive styles. In our evaluation, we used data collected from intelligence analysts, and simulated malicious insiders based on this data. A high percentage of the simulated malicious insiders were successfully detected.","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":"131447985","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}
Two important factors which indirectly influence the Internet shoppers to make some online purchases are the visual layout and the presentation of web page. In this paper, we propose an approach of web page layout analysis in order to assess the design of e-commerce Web sites. Firstly, our proposed method segments each web page into five different blocks: top, left, center, right and bottom. We study three main feature types: spatial, location and presentation, which effect the design of each page. The spatial feature set includes the width-length ratio and relative area of each block while the location feature set is the appearance positions of e-commerce components such as navigation, product index and customer service. The presentation feature set represents page characteristic and navigation menu format that appear on the page or block such as navigator style, menu type, image alignment and text density. To perform the experiments, we consider the top 100 Internet retailers as ranked by the Internet Retailerpsilas Top 500 Guide. We adopt classification algorithms in order to construct a model from the top Web sites against other 100 randomly selected e-commerce Web sites. The experimental results showed that the model which is constructed based on the presentation feature set yields better performance than using the spatial and location feature sets.
{"title":"An Analysis of Visual and Presentation Factors Influencing the Design of E-commerce Web Sites","authors":"Banatus Soiraya, A. Mingkhwan, C. Haruechaiyasak","doi":"10.1109/WIIAT.2008.213","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.213","url":null,"abstract":"Two important factors which indirectly influence the Internet shoppers to make some online purchases are the visual layout and the presentation of web page. In this paper, we propose an approach of web page layout analysis in order to assess the design of e-commerce Web sites. Firstly, our proposed method segments each web page into five different blocks: top, left, center, right and bottom. We study three main feature types: spatial, location and presentation, which effect the design of each page. The spatial feature set includes the width-length ratio and relative area of each block while the location feature set is the appearance positions of e-commerce components such as navigation, product index and customer service. The presentation feature set represents page characteristic and navigation menu format that appear on the page or block such as navigator style, menu type, image alignment and text density. To perform the experiments, we consider the top 100 Internet retailers as ranked by the Internet Retailerpsilas Top 500 Guide. We adopt classification algorithms in order to construct a model from the top Web sites against other 100 randomly selected e-commerce Web sites. The experimental results showed that the model which is constructed based on the presentation feature set yields better performance than using the spatial and location feature sets.","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":"134442278","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 threaded discussion communities are one of the most common forms of online communities, which are becoming more and more popular among web users. Everyday a huge amount of new discussions are added to these communities, which are difficult to summarize and search. In this paper, we propose a topic detection and tracking (TDT) method for the discussion threads. Most existing TDT methods deal with the news stories, but the language used in discussion data are much more casual, oral and informal compared with news data. To solve this problem, we design several extensions to the basic TDT framework, focusing on the very nature of discussion data, including a thread/post activity validation step, a term pos-weighting strategy, and a two-level decision framework considering not only the content similarity but also the user activity information. Experiment results show that our pro-posed method greatly improves current TDT methods in real discussion community environment. The discussion data can be better organized for searching and visualization with the help of TDT.
{"title":"Topic Detection and Tracking for Threaded Discussion Communities","authors":"Mingliang Zhu, Weiming Hu, Ou Wu","doi":"10.1109/WIIAT.2008.50","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.50","url":null,"abstract":"The threaded discussion communities are one of the most common forms of online communities, which are becoming more and more popular among web users. Everyday a huge amount of new discussions are added to these communities, which are difficult to summarize and search. In this paper, we propose a topic detection and tracking (TDT) method for the discussion threads. Most existing TDT methods deal with the news stories, but the language used in discussion data are much more casual, oral and informal compared with news data. To solve this problem, we design several extensions to the basic TDT framework, focusing on the very nature of discussion data, including a thread/post activity validation step, a term pos-weighting strategy, and a two-level decision framework considering not only the content similarity but also the user activity information. Experiment results show that our pro-posed method greatly improves current TDT methods in real discussion community environment. The discussion data can be better organized for searching and visualization with the help of TDT.","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":"134453123","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}
J. Eckert, D. Ertogrul, André Miede, N. Repp, R. Steinmetz
Resource allocation and resource planning, especially in a SOA and grid environment, become crucial. Particularly, in an environment with a huge number of workflow consumers requesting a decentralized cross-organizational workflow, performance evaluation and execution-management of service-oriented workflows gain in importance. The need for an effective and efficient workflow management forces enterprises to use intelligent optimization models and heuristics to compose workflows out of several services under real-time conditions. This paper introduces the required architecture workflow performance extension - WPX.KOM for resource planning and workload prediction purposes. Furthermore, optimization approaches and a high-performance heuristic solving the addressed resource planning problem with low computational overhead are presented.
{"title":"Resource Planning Heuristics for Service-Oriented Workflows","authors":"J. Eckert, D. Ertogrul, André Miede, N. Repp, R. Steinmetz","doi":"10.1109/WIIAT.2008.108","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.108","url":null,"abstract":"Resource allocation and resource planning, especially in a SOA and grid environment, become crucial. Particularly, in an environment with a huge number of workflow consumers requesting a decentralized cross-organizational workflow, performance evaluation and execution-management of service-oriented workflows gain in importance. The need for an effective and efficient workflow management forces enterprises to use intelligent optimization models and heuristics to compose workflows out of several services under real-time conditions. This paper introduces the required architecture workflow performance extension - WPX.KOM for resource planning and workload prediction purposes. Furthermore, optimization approaches and a high-performance heuristic solving the addressed resource planning problem with low computational overhead are presented.","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":"131762041","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 study and compare three different but related types of metadata about Web documents: social annotations provided by readers of Web documents, hyperlink anchor text provided by authors of Web documents, and search queries of users trying to find Web documents. We introduce a large research data set called CABS120k, which we have created for this study from a variety of information sources such as AOL500k, the Open Directory Project, del.icio.us/Yahoo!, Google and the WWW in general. We use this data set to investigate several characteristics of said metadata including length, novelty, diversity, and similarity and discuss theoretical and practical implications.
{"title":"The Metadata Triumvirate: Social Annotations, Anchor Texts and Search Queries","authors":"Michael G. Noll, C. Meinel","doi":"10.1109/WIIAT.2008.341","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.341","url":null,"abstract":"In this paper, we study and compare three different but related types of metadata about Web documents: social annotations provided by readers of Web documents, hyperlink anchor text provided by authors of Web documents, and search queries of users trying to find Web documents. We introduce a large research data set called CABS120k, which we have created for this study from a variety of information sources such as AOL500k, the Open Directory Project, del.icio.us/Yahoo!, Google and the WWW in general. We use this data set to investigate several characteristics of said metadata including length, novelty, diversity, and similarity and discuss theoretical and practical implications.","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":"130958538","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 systematic, reasoner-aided approach to Web ontology acquisition and refinement. It complements methods for acquiring expressive ontology axioms from textual definitions with methodic knowledge exploration techniques based on formal concept analysis. We demonstrate the practical relevance of our approach by means of a real-world example.
{"title":"Fostering Web Intelligence by Semi-automatic OWL Ontology Refinement","authors":"Johanna Völker, S. Rudolph","doi":"10.1109/WIIAT.2008.36","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.36","url":null,"abstract":"In this paper, we propose a systematic, reasoner-aided approach to Web ontology acquisition and refinement. It complements methods for acquiring expressive ontology axioms from textual definitions with methodic knowledge exploration techniques based on formal concept analysis. We demonstrate the practical relevance of our approach by means of a real-world example.","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":"132823947","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}
Plagiarism is a serious problem that infringes copyrighted documents/materials, which is an unethical practice and decreases the economic incentive received by authors (owners) of the original copies. Unfortunately, plagiarism is getting worse due to the increasing number of on-line publications on the Web, which facilitates locating and paraphrasing information. In solving this problem, we propose a novel plagiarism-detection method, called SimPaD, which (i) establishes the degree of resemblance between any two documents D1 and D2 based on their sentence-to-sentence similarity computed by using pre-defined word-correlation factors, and (ii) generates agraphical view of sentences that are similar (or the same) in D1 and D2. Experimental results verify that SimPaD is highly accurate in detecting (non-) plagiarized documents and outperforms existing plagiarism-detection approaches.
{"title":"Nowhere to Hide: Finding Plagiarized Documents Based on Sentence Similarity","authors":"Nathaniel Gustafson, M. S. Pera, Yiu-Kai Ng","doi":"10.1109/WIIAT.2008.16","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.16","url":null,"abstract":"Plagiarism is a serious problem that infringes copyrighted documents/materials, which is an unethical practice and decreases the economic incentive received by authors (owners) of the original copies. Unfortunately, plagiarism is getting worse due to the increasing number of on-line publications on the Web, which facilitates locating and paraphrasing information. In solving this problem, we propose a novel plagiarism-detection method, called SimPaD, which (i) establishes the degree of resemblance between any two documents D1 and D2 based on their sentence-to-sentence similarity computed by using pre-defined word-correlation factors, and (ii) generates agraphical view of sentences that are similar (or the same) in D1 and D2. Experimental results verify that SimPaD is highly accurate in detecting (non-) plagiarized documents and outperforms existing plagiarism-detection approaches.","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":"132824499","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}
Wei Chen, Lijun Zhang, C. Wang, Chun Chen, Jiajun Bu
It is very difficult for blind and visually-impaired people getting information from the outside world. In this paper, we propose an adaptive Web news recommendation system named EagleRadio, designed for blind man and supports pervasive access using terminals. EagleRadio offers natural and user-friendly interface. News stories from different topics are read via a speech synthesizer to users and they can use commands to navigate inside the news space. Based on the analyzing of userpsilas listening history, adaptive topic navigation and news recommendation methods help users reaching relevant topics quickly and push the most relevant news to them. Finally, we evaluate the proposed algorithms and quantify the effect of EagleRadio from a userpsilas perspective.
{"title":"Pervasive Web News Recommendation for Visually Impaired People","authors":"Wei Chen, Lijun Zhang, C. Wang, Chun Chen, Jiajun Bu","doi":"10.1109/WIIAT.2008.43","DOIUrl":"https://doi.org/10.1109/WIIAT.2008.43","url":null,"abstract":"It is very difficult for blind and visually-impaired people getting information from the outside world. In this paper, we propose an adaptive Web news recommendation system named EagleRadio, designed for blind man and supports pervasive access using terminals. EagleRadio offers natural and user-friendly interface. News stories from different topics are read via a speech synthesizer to users and they can use commands to navigate inside the news space. Based on the analyzing of userpsilas listening history, adaptive topic navigation and news recommendation methods help users reaching relevant topics quickly and push the most relevant news to them. Finally, we evaluate the proposed algorithms and quantify the effect of EagleRadio from a userpsilas perspective.","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":"133572729","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：