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}
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}
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}
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}
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}
This paper introduces MinCor (Minimum of Correlations), a decentralized simulated annealing algorithm designed for the data placement in peer-to-peer networks. Its goal is to reduce the correlated failures impact in such data storage systems. This data placement is realized using a multi-agent system which turns the documents into mobile agents flocks. After a network clustering step where highly correlated peers are regrouped together, the flocks executing MinCor are able to find a placement minimizing the number of agents on the same clusters. This placement is obtained in a decentralized way thanks to the environment exploration capabilities of the flocks. A set of experiments are performed on this system in presence of correlated failures. They show that, in practice, the expected placement is well obtained. They also show that, flocks using the MinCor algorithm suffer less simultaneous losses in presence of correlated failures than a mere random placement.
本文介绍了一种用于点对点网络中数据放置的去中心化模拟退火算法MinCor (Minimum of correlation)。其目标是减少此类数据存储系统中相关故障的影响。这种数据放置是使用多代理系统实现的，该系统将文档转换为移动代理群。在将高度相关的节点重新组合在一起的网络聚类步骤之后，执行MinCor的群能够找到最小化同一集群上代理数量的放置。由于羊群的环境探索能力，这种安置是以分散的方式获得的。在存在相关故障的情况下，对该系统进行了一组实验。它们表明，在实践中，预期的安置是很好的。他们还表明，与随机放置相比，使用MinCor算法的鸟群在存在相关故障时遭受的同时损失更少。
{"title":"Reducing Correlated Failures Impact in Peer-to-Peer Storage Systems Using Mobile Agents Flocks","authors":"Benoît Romito, F. Bourdon","doi":"10.1109/WI-IAT.2012.17","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.17","url":null,"abstract":"This paper introduces MinCor (Minimum of Correlations), a decentralized simulated annealing algorithm designed for the data placement in peer-to-peer networks. Its goal is to reduce the correlated failures impact in such data storage systems. This data placement is realized using a multi-agent system which turns the documents into mobile agents flocks. After a network clustering step where highly correlated peers are regrouped together, the flocks executing MinCor are able to find a placement minimizing the number of agents on the same clusters. This placement is obtained in a decentralized way thanks to the environment exploration capabilities of the flocks. A set of experiments are performed on this system in presence of correlated failures. They show that, in practice, the expected placement is well obtained. They also show that, flocks using the MinCor algorithm suffer less simultaneous losses in presence of correlated failures than a mere random placement.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"323 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":"123649559","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}
Location information is becoming prevalent in today's online social networks (OSNs), which raises special privacy concerns with regard to both location sharing and its applications. Even when no explicit location is disclosed by a user, it is possible to geolocate the user through his/her social context, e.g., status updates and social relationships in OSNs. To demonstrate this, we propose GeoFind, which accurately identifies users' geographic regions through effective fusion (re-ranking) of (1) text-based ranking using geo-sensitive textual features and (2) structure-based ranking using maximum likelihood estimation (MLE) of geotagged friends. Evaluation results using 0.8 million geotagged Twitter users over a 3-month period demonstrate that GeoFind outperforms state-of-the-art techniques, with significant reduction of estimation error (25% of average error, 66% of median error). The potential of improving location accuracy through the fusion of multiple data types calls for a re-examination of existing privacy protection policies and mechanisms.
{"title":"Fusing Text and Frienships for Location Inference in Online Social Networks","authors":"Hansu Gu, Haojie Hang, Q. Lv, D. Grunwald","doi":"10.1109/WI-IAT.2012.243","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.243","url":null,"abstract":"Location information is becoming prevalent in today's online social networks (OSNs), which raises special privacy concerns with regard to both location sharing and its applications. Even when no explicit location is disclosed by a user, it is possible to geolocate the user through his/her social context, e.g., status updates and social relationships in OSNs. To demonstrate this, we propose GeoFind, which accurately identifies users' geographic regions through effective fusion (re-ranking) of (1) text-based ranking using geo-sensitive textual features and (2) structure-based ranking using maximum likelihood estimation (MLE) of geotagged friends. Evaluation results using 0.8 million geotagged Twitter users over a 3-month period demonstrate that GeoFind outperforms state-of-the-art techniques, with significant reduction of estimation error (25% of average error, 66% of median error). The potential of improving location accuracy through the fusion of multiple data types calls for a re-examination of existing privacy protection policies and mechanisms.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"3 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":"125143470","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}
Virtual learning environments (VLEs) are online learning systems that are used to enhance a student's learning experience by providing a set of teaching, learning and communication tools. The current VLEs, however, are not fully utilised or exploited to support effective collaborative learning. This paper investigates how to build effective online collaborative virtual learning environments, by exploring the requirements of VLEs from personal users. A prototype is then created to show how the designs of current VLEs can be improved to provide the essential functionalities and ease of use.
{"title":"Investigation and Prototype Design of Collaborative Virtual Learning Enivronments","authors":"M. Darwaish, Fang Wang","doi":"10.1109/WI-IAT.2012.176","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.176","url":null,"abstract":"Virtual learning environments (VLEs) are online learning systems that are used to enhance a student's learning experience by providing a set of teaching, learning and communication tools. The current VLEs, however, are not fully utilised or exploited to support effective collaborative learning. This paper investigates how to build effective online collaborative virtual learning environments, by exploring the requirements of VLEs from personal users. A prototype is then created to show how the designs of current VLEs can be improved to provide the essential functionalities and ease of use.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"16 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":"129835820","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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