Many relations existing in DBpedia are missing in Wikipedia yielding up an information gap between the semantic web and the social web. Inserting these missing relations requires to automatically discover Wikipedia conventions. From pairs linked by a property p in DBpedia, we find path queries that link the same pairs in Wikipedia. We make the hypothesis that the shortest path query with maximal containment captures the Wikipedia convention for p. We computed missing links and conventions for different DBpedia queries. Next, we inserted some missing links according to computed conventions in Wikipedia and evaluated Wikipedians feedback. Nearly all contributions has been accepted. In this paper, we detail the path indexing algorithms, the results of evaluations and give some details about social feedback.
{"title":"From DBpedia to Wikipedia: Filling the Gap by Discovering Wikipedia Conventions","authors":"Diego Torres, P. Molli, H. Skaf-Molli, A. Díaz","doi":"10.5555/2457524.2457642","DOIUrl":"https://doi.org/10.5555/2457524.2457642","url":null,"abstract":"Many relations existing in DBpedia are missing in Wikipedia yielding up an information gap between the semantic web and the social web. Inserting these missing relations requires to automatically discover Wikipedia conventions. From pairs linked by a property p in DBpedia, we find path queries that link the same pairs in Wikipedia. We make the hypothesis that the shortest path query with maximal containment captures the Wikipedia convention for p. We computed missing links and conventions for different DBpedia queries. Next, we inserted some missing links according to computed conventions in Wikipedia and evaluated Wikipedians feedback. Nearly all contributions has been accepted. In this paper, we detail the path indexing algorithms, the results of evaluations and give some details about social feedback.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134604698","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}
With the increasing popularity of the Semantic Web, more and more data models are being published daily in the form of ontologies, micro-formats or micro-data. This increase in the amount of models and their heterogeneity is becoming a global scale integration problem. We propose a decentralized and scalable multi-agent negotiation process for ontology alignment that exploits an underlying social network communication structure and SNA measures and algorithms.
{"title":"Social Networked Multi-agent Negotiation in Ontology Alignment","authors":"Nuno Luz, Nuno Silva, P. Novais","doi":"10.1109/WI-IAT.2012.125","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.125","url":null,"abstract":"With the increasing popularity of the Semantic Web, more and more data models are being published daily in the form of ontologies, micro-formats or micro-data. This increase in the amount of models and their heterogeneity is becoming a global scale integration problem. We propose a decentralized and scalable multi-agent negotiation process for ontology alignment that exploits an underlying social network communication structure and SNA measures and algorithms.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133109068","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 forums have become a major source of information gathering/mining due to a large amount of user generated content. Crawling of web forums is necessary to gather/mine the information from them. However, a generic web crawler is unable to efficiently and effectively crawl the web forums because of the existence of many redundant and duplicate pages. In addition, there exists a crawling relationship among the useful pages that need to be considered. So, for efficient crawling, we need to intelligently crawl the web forums by eliminating redundant and duplicate pages, and understanding the crawling relationship. Existing works in forum crawling use visual pattern recognition based methods, which make them extremely computational expensive. In this paper, we propose a novel light-weight crawling method using text and links properties of the pages in web forums. Theoretical analysis and experimental results show the effectiveness and efficiency of the proposed method.
{"title":"A Generalized Links and Text Properties Based Forum Crawler","authors":"Amit Sachan, Wee-Yong Lim, V. Thing","doi":"10.1109/WI-IAT.2012.213","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.213","url":null,"abstract":"Web forums have become a major source of information gathering/mining due to a large amount of user generated content. Crawling of web forums is necessary to gather/mine the information from them. However, a generic web crawler is unable to efficiently and effectively crawl the web forums because of the existence of many redundant and duplicate pages. In addition, there exists a crawling relationship among the useful pages that need to be considered. So, for efficient crawling, we need to intelligently crawl the web forums by eliminating redundant and duplicate pages, and understanding the crawling relationship. Existing works in forum crawling use visual pattern recognition based methods, which make them extremely computational expensive. In this paper, we propose a novel light-weight crawling method using text and links properties of the pages in web forums. Theoretical analysis and experimental results show the effectiveness and efficiency of the proposed method.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129101389","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}
Recently, named entity recognition tools tend to disambiguate recognized named entities on a very detailed level. Instead of elementary types (e.g. Person or Location), they assign concrete identifiers, trying to distinguish even different entities having same name and type (e.g. cities with the same name in different countries). We introduce a novel method for this kind of named entity disambiguation exploiting structural dependencies of recognized entities. We analyse the co-occurrence of disambiguated entities in the backing knowledge base and use this information to improve results of existing named entity disambiguation approaches. A model for co-occurrence representation is proposed and evaluated based on a dataset that we mine from Wikipedia.
{"title":"Context Aware Named Entity Disambiguation","authors":"Ivo Lasek, P. Vojtás","doi":"10.1109/WI-IAT.2012.96","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.96","url":null,"abstract":"Recently, named entity recognition tools tend to disambiguate recognized named entities on a very detailed level. Instead of elementary types (e.g. Person or Location), they assign concrete identifiers, trying to distinguish even different entities having same name and type (e.g. cities with the same name in different countries). We introduce a novel method for this kind of named entity disambiguation exploiting structural dependencies of recognized entities. We analyse the co-occurrence of disambiguated entities in the backing knowledge base and use this information to improve results of existing named entity disambiguation approaches. A model for co-occurrence representation is proposed and evaluated based on a dataset that we mine from Wikipedia.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132032196","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 novel skin segmentation scheme based on human face illumination feature is proposed in this paper. First, we perform a face detection in order to measure the face position and amount on image, and then analyze each face's illumination feature. According these parameters, we classify the skin pixel and generate skin probability map, and finally fetch out a prefect skin mask for skin segmentation. Experimental results based on common dataset show that the proposed method can achieve 92.83% true positive rate (TPR) with 15.82% false positive rate (FPR), outperforming the traditional GMM skin segmentation method.
{"title":"Skin Segmentation Based on Human Face Illumination Feature","authors":"Pan Ng, Chi-Man Pun","doi":"10.1109/WI-IAT.2012.71","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.71","url":null,"abstract":"A novel skin segmentation scheme based on human face illumination feature is proposed in this paper. First, we perform a face detection in order to measure the face position and amount on image, and then analyze each face's illumination feature. According these parameters, we classify the skin pixel and generate skin probability map, and finally fetch out a prefect skin mask for skin segmentation. Experimental results based on common dataset show that the proposed method can achieve 92.83% true positive rate (TPR) with 15.82% false positive rate (FPR), outperforming the traditional GMM skin segmentation method.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117189721","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}
Andreas Emrich, Alexandra Chapko, Dirk Werth, P. Loos
This paper introduces a preliminary approach and evaluation for a social recommendation mechanism for location-based services (LBS). Many approaches for recommending location-based services do not take into account other factors than spatial ones. This paper focuses on social interactions and a focused ranking method to support social recommendations. The qualitative and quantitative evaluation at the end of the paper demonstrates, that users find social recommendations more useful than the conventional ones.
{"title":"Social Recommendations for Location-Based Services","authors":"Andreas Emrich, Alexandra Chapko, Dirk Werth, P. Loos","doi":"10.1109/WI-IAT.2012.238","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.238","url":null,"abstract":"This paper introduces a preliminary approach and evaluation for a social recommendation mechanism for location-based services (LBS). Many approaches for recommending location-based services do not take into account other factors than spatial ones. This paper focuses on social interactions and a focused ranking method to support social recommendations. The qualitative and quantitative evaluation at the end of the paper demonstrates, that users find social recommendations more useful than the conventional ones.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115396480","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}
Content is most important element on any website. Keyword based reports, obtained from web analytics tools, provide insight to content usability of website. In this paper a tool 'Keyword Similarly Measure Tool'(KSMT) is presented which can be used to optimize the Keyword based report by combining the similar keyword that have relevant meaning and get a closer and concise picture. The aim is to improve the data accuracy and overcome limitation of similar keywords being vastly separated in the report. This way the methodology also provides holistic view of the data for similar keywords, by combining the matrices like bounce-rate, visits for the similar keywords and hence aim to provide a collective view and content analysis. The methodology also provides a way to compare & analyze Keywords with 'Suggested Keyword' provided by the user. The KSMT tool is developed using Perl, Apache and flex.
{"title":"A Website Content Analysis Approach Based on Keyword Similarity Analysis","authors":"Shruti Kohli, Sandeep Kaur, G. Singh","doi":"10.1109/WI-IAT.2012.212","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.212","url":null,"abstract":"Content is most important element on any website. Keyword based reports, obtained from web analytics tools, provide insight to content usability of website. In this paper a tool 'Keyword Similarly Measure Tool'(KSMT) is presented which can be used to optimize the Keyword based report by combining the similar keyword that have relevant meaning and get a closer and concise picture. The aim is to improve the data accuracy and overcome limitation of similar keywords being vastly separated in the report. This way the methodology also provides holistic view of the data for similar keywords, by combining the matrices like bounce-rate, visits for the similar keywords and hence aim to provide a collective view and content analysis. The methodology also provides a way to compare & analyze Keywords with 'Suggested Keyword' provided by the user. The KSMT tool is developed using Perl, Apache and flex.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"316 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115623378","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}
Currently, people around the world are suffering from mental disorders. Given the wide-spread use of the Internet, we propose to predict users' mental health status based on browsing behavior, and further recommend suggestions for adjustment. To identify mental health status, we extract the user's web browsing behavior, and train a Support Vector Machine(SVM) model for prediction. Based on the predicted status, our recommender system generates suggestions for adjusting mental disorders. We have implemented a system named Web Mind as the experimental platform integrated with the predicting model and recommendation engine. We have conducted user study to test the effectiveness of the predicting model, and the result demonstrates that the recommender system performs fairly well.
{"title":"Predicting Mental Health Status in the Context of Web Browsing","authors":"Dong Nie, Yue Ning, T. Zhu","doi":"10.1109/WI-IAT.2012.196","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.196","url":null,"abstract":"Currently, people around the world are suffering from mental disorders. Given the wide-spread use of the Internet, we propose to predict users' mental health status based on browsing behavior, and further recommend suggestions for adjustment. To identify mental health status, we extract the user's web browsing behavior, and train a Support Vector Machine(SVM) model for prediction. Based on the predicted status, our recommender system generates suggestions for adjusting mental disorders. We have implemented a system named Web Mind as the experimental platform integrated with the predicting model and recommendation engine. We have conducted user study to test the effectiveness of the predicting model, and the result demonstrates that the recommender system performs fairly well.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123485703","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 repeated multi-agent constant-sum games, each player's objective is to maximize control over a finite set of resources. We introduce Tens potter, an easy-to-use publicly-available game designed to allow human players to compete as agents against a machine algorithm. The algorithm learns play strategies from humans, reduces them to nine basic strategies, and uses this knowledge to build and adapt its collusion strategy. We use a tournament format to test our algorithm against human players as well as against other established multi-agent algorithms taken from the literature. Through these tournament experiments, we demonstrate how learning techniques adapted using human computation -- information obtained from both human and machine inputs -- can contribute to the development of an algorithm able to defeat two well-established multi-agent machine algorithms in tournament play.
{"title":"Developing a Repeated Multi-agent Constant-Sum Game Algorithm Using Human Computation","authors":"Christopher G. Harris","doi":"10.1109/WI-IAT.2012.175","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.175","url":null,"abstract":"In repeated multi-agent constant-sum games, each player's objective is to maximize control over a finite set of resources. We introduce Tens potter, an easy-to-use publicly-available game designed to allow human players to compete as agents against a machine algorithm. The algorithm learns play strategies from humans, reduces them to nine basic strategies, and uses this knowledge to build and adapt its collusion strategy. We use a tournament format to test our algorithm against human players as well as against other established multi-agent algorithms taken from the literature. Through these tournament experiments, we demonstrate how learning techniques adapted using human computation -- information obtained from both human and machine inputs -- can contribute to the development of an algorithm able to defeat two well-established multi-agent machine algorithms in tournament play.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124399899","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}
Since its creation, the Asynchronous Partial Overlay (APO) protocol has received a great deal of attention because of its non-traditional approach to solving Distributed Constraint Satisfaction Problems (DCSPs). Its introduction led investigators to question the very definition of the word "distributed" and has subsequently inspired the community to create improved metrics for parallel computation, enhanced testing procedures, and most importantly new DCSP algorithms. These advances have raised concerns about APO's parallel efficiency by showing that, in some cases, APO performs very poorly compared to protocols such as Asynchronous Forward Checking, Conflict-directed Back jumping (AFC-CBJ). In addition, APO's soundness and completeness were brought into question when it was discovered that, under certain conditions, stale state information could cause the protocol's distributed locking mechanism to fail. This work revisits APO by reengineering the protocol to simplify it and increase its parallelism while ensuring its soundness and completeness. It also vastly improves the parallel efficiency of APO by replacing its central solver with a variant of the Forward Checking, Conflict-directed Back jumping (FC-CBJ) algorithm that is specifically tuned to complement the heuristic strategies used by APO to limit its centralization. This new version of APO is then evaluated against the AFC-CBJ protocol using random instances of both DCSPs and distributed 3-coloring problems. The end result is a protocol that is several orders of magnitude faster than the original APO, uses less messages, is more private, and outperforms the AFC-CBJ protocol in nearly every case tested.
{"title":"Improving Asynchronous Partial Overlay","authors":"R. Mailler","doi":"10.1109/WI-IAT.2012.100","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.100","url":null,"abstract":"Since its creation, the Asynchronous Partial Overlay (APO) protocol has received a great deal of attention because of its non-traditional approach to solving Distributed Constraint Satisfaction Problems (DCSPs). Its introduction led investigators to question the very definition of the word \"distributed\" and has subsequently inspired the community to create improved metrics for parallel computation, enhanced testing procedures, and most importantly new DCSP algorithms. These advances have raised concerns about APO's parallel efficiency by showing that, in some cases, APO performs very poorly compared to protocols such as Asynchronous Forward Checking, Conflict-directed Back jumping (AFC-CBJ). In addition, APO's soundness and completeness were brought into question when it was discovered that, under certain conditions, stale state information could cause the protocol's distributed locking mechanism to fail. This work revisits APO by reengineering the protocol to simplify it and increase its parallelism while ensuring its soundness and completeness. It also vastly improves the parallel efficiency of APO by replacing its central solver with a variant of the Forward Checking, Conflict-directed Back jumping (FC-CBJ) algorithm that is specifically tuned to complement the heuristic strategies used by APO to limit its centralization. This new version of APO is then evaluated against the AFC-CBJ protocol using random instances of both DCSPs and distributed 3-coloring problems. The end result is a protocol that is several orders of magnitude faster than the original APO, uses less messages, is more private, and outperforms the AFC-CBJ protocol in nearly every case tested.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124782730","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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