André Luis Schwerz, Rafael Liberato, I. Wiese, Igor Steinmacher, M. Gerosa, J. E. Ferreira
Developers of distributed open source projects use management and issues tracking tool to communicate. These tools provide a large volume of unstructured information that makes the triage of issues difficult, increasing developers' overhead. This problem is common to online communities based on volunteer participation. This paper shows the importance of the content of comments in an open source project to build a classifier to predict the participation for a developer in an issue. To design this prediction model, we used two machine learning algorithms called Naive Bayes and J48. We used the data of three Apache Hadoop subprojects to evaluate the use of the algorithms. By applying our approach to the most active developers of these subprojects we have achieved an accuracy ranging from 79% to 96%. The results indicate that the content of comments in issues of open source projects is a relevant factor to build a classifier of issues for developers.
{"title":"Prediction of Developer Participation in Issues of Open Source Projects","authors":"André Luis Schwerz, Rafael Liberato, I. Wiese, Igor Steinmacher, M. Gerosa, J. E. Ferreira","doi":"10.1109/SBSC.2012.27","DOIUrl":"https://doi.org/10.1109/SBSC.2012.27","url":null,"abstract":"Developers of distributed open source projects use management and issues tracking tool to communicate. These tools provide a large volume of unstructured information that makes the triage of issues difficult, increasing developers' overhead. This problem is common to online communities based on volunteer participation. This paper shows the importance of the content of comments in an open source project to build a classifier to predict the participation for a developer in an issue. To design this prediction model, we used two machine learning algorithms called Naive Bayes and J48. We used the data of three Apache Hadoop subprojects to evaluate the use of the algorithms. By applying our approach to the most active developers of these subprojects we have achieved an accuracy ranging from 79% to 96%. The results indicate that the content of comments in issues of open source projects is a relevant factor to build a classifier of issues for developers.","PeriodicalId":257965,"journal":{"name":"2012 Brazilian Symposium on Collaborative Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133906847","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 expansion of the Internet and the growing use of social networks, allowed the capture and use of data related to traffic. This article presents an application, based in an intelligent system that explores the cooperativity of Facebook users so that, by data mining, get a navigable map that points out the most recent transit events reported by users. Thus, it is expected to contribute with useful information that helps any user to take decisions about the best path to be performed for his locomotion, avoiding, for example, traffic jams or accidents that are blocking roads they normally use.
{"title":"A System to Capture and Generation of Traffic Information from Posted Messages on Social Networks","authors":"E. Huzita, T. G. D. Souza, Yan H. Kabuki","doi":"10.1109/SBSC.2012.25","DOIUrl":"https://doi.org/10.1109/SBSC.2012.25","url":null,"abstract":"The expansion of the Internet and the growing use of social networks, allowed the capture and use of data related to traffic. This article presents an application, based in an intelligent system that explores the cooperativity of Facebook users so that, by data mining, get a navigable map that points out the most recent transit events reported by users. Thus, it is expected to contribute with useful information that helps any user to take decisions about the best path to be performed for his locomotion, avoiding, for example, traffic jams or accidents that are blocking roads they normally use.","PeriodicalId":257965,"journal":{"name":"2012 Brazilian Symposium on Collaborative Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131855347","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}
Recommendation systems allow users to deal with information overload by generating personalized recommendations that guide them through the universe of available options. These systems have been successfully used for over a decade in various application domains. However, most recommendation techniques do not consider context, generating recommendations which do not consider user's daily generated information. The increasing use of social networks and microblogs has created a valuable source to extract information that might help improve the results of recommender systems. Specifically, microblogging messages may help on contextualized movie recommendation. In this paper, a hybrid recommender is proposed merging a collaborative filtering recommender with a content based recommender. The results confirm the usefulness of the proposed recommender, where the user's exchanged messages define a bias to insert context in the recommendations.
{"title":"May Social Behavior Reveal Preferences on Different Contexts? Recommending Movie Titles Based on Tweets","authors":"F. H. Borsato, Ivanilton Polato","doi":"10.1109/SBSC.2012.18","DOIUrl":"https://doi.org/10.1109/SBSC.2012.18","url":null,"abstract":"Recommendation systems allow users to deal with information overload by generating personalized recommendations that guide them through the universe of available options. These systems have been successfully used for over a decade in various application domains. However, most recommendation techniques do not consider context, generating recommendations which do not consider user's daily generated information. The increasing use of social networks and microblogs has created a valuable source to extract information that might help improve the results of recommender systems. Specifically, microblogging messages may help on contextualized movie recommendation. In this paper, a hybrid recommender is proposed merging a collaborative filtering recommender with a content based recommender. The results confirm the usefulness of the proposed recommender, where the user's exchanged messages define a bias to insert context in the recommendations.","PeriodicalId":257965,"journal":{"name":"2012 Brazilian Symposium on Collaborative Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130116302","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 research reports on autism, music therapy and immersive collaborative systems, defining and proposing a collaborative system for immersive music, the Music Spectrum, assisting in development of communication skills, imagination and social interaction of children with autism.
{"title":"Music Spectrum: A Collaborative Immersion Musical System for Children with Autism","authors":"David Lima, Thais Castro","doi":"10.1109/SBSC.2012.33","DOIUrl":"https://doi.org/10.1109/SBSC.2012.33","url":null,"abstract":"This research reports on autism, music therapy and immersive collaborative systems, defining and proposing a collaborative system for immersive music, the Music Spectrum, assisting in development of communication skills, imagination and social interaction of children with autism.","PeriodicalId":257965,"journal":{"name":"2012 Brazilian Symposium on Collaborative Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131827347","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}
Vaninha Vieira, Adriano Fialho, Victor Martinez, Jailson Brito, Lincoln Brito, Adolfo Duran
Urban mobility is an issue that, in general, makes citizens daily life stressful and complicated. Crowd sourcing-based systems promote what is called "the power of the citizens", stimulating people to contribute on solving public and governmental problems, being mobility one of them. In our project, named Ubibus, we investigate how crowd sourcing can be applied to improve public transportation. In this paper, we propose the use of collaborative riding as a complementary alternative to public transportation, integrating private and public vehicles. We also investigate what can motivate people to participate in such a system, and how Gamification techniques can be used to improve the adherence to the system usage. In order to evaluate the subject and to understand the actual problems as regular people see it, we conducted two exploratory studies with passengers and drivers. The first one is composed by an online questionnaire, answered by Brazilian people, and the second one is a field study conducted with two groups of students at our University. This paper aims to present the performed studies and to discuss the results achieved with them, which were used as requirements to guide the design of a collaborative riding system.
{"title":"An Exploratory Study on the Use of Collaborative Riding Based on Gamification as a Support to Public Transportation","authors":"Vaninha Vieira, Adriano Fialho, Victor Martinez, Jailson Brito, Lincoln Brito, Adolfo Duran","doi":"10.1109/SBSC.2012.32","DOIUrl":"https://doi.org/10.1109/SBSC.2012.32","url":null,"abstract":"Urban mobility is an issue that, in general, makes citizens daily life stressful and complicated. Crowd sourcing-based systems promote what is called \"the power of the citizens\", stimulating people to contribute on solving public and governmental problems, being mobility one of them. In our project, named Ubibus, we investigate how crowd sourcing can be applied to improve public transportation. In this paper, we propose the use of collaborative riding as a complementary alternative to public transportation, integrating private and public vehicles. We also investigate what can motivate people to participate in such a system, and how Gamification techniques can be used to improve the adherence to the system usage. In order to evaluate the subject and to understand the actual problems as regular people see it, we conducted two exploratory studies with passengers and drivers. The first one is composed by an online questionnaire, answered by Brazilian people, and the second one is a field study conducted with two groups of students at our University. This paper aims to present the performed studies and to discuss the results achieved with them, which were used as requirements to guide the design of a collaborative riding system.","PeriodicalId":257965,"journal":{"name":"2012 Brazilian Symposium on Collaborative Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124378927","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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