Purpose:To have a better understanding of library users' social bookmarking behaviors,we conducted a survey of college students to examine how much attention they have paid to social bookmarking results,their soci...Purpose:To have a better understanding of library users' social bookmarking behaviors,we conducted a survey of college students to examine how much attention they have paid to social bookmarking results,their social bookmarking motivations and behaviors on book sharing sites and in their library's OPAC,and their expectations to their library's social bookmarking service.Design/methodology/approach:A questionnaire survey was conducted to investigate social bookmarking behaviors and motivations of users of Wuhan University Library(WUL) on book sharing sites and in WUL's OPAC.A total of 700 questionnaires were distributed and357 valid questionnaires were retrieved.SPSS was used for data analysis.Findings:The results revealed that there were differences between users' social bookmarking behaviors on book sharing sites and in the Library's OPAC.Users preferred to use tags than add tags on book sharing sites.The main tagging motivation on book sharing sites was for meeting users' specific needs such as collection management and book recommendations.As for the Library,the lack of publicity and promotion of the social bookmarking service led to insufficient use of the Library's service.Due to a lack of knowledge of the social bookmarking service,users did not care about the lectures or publicity campaigns about the Library's social bookmarking service.Research limitations:Because social bookmarking was not common among WUL users,and the questionnaires could be handed out to a limited number of people,it was hard to describe users' social bookmarking behaviors in the Library's OPAC by investigating a sample of 357Library users,and therefore we only investigated users' social bookmarking behaviors on the book sharing sites.Practical implications:The survey results provide insights into library users' social bookmarking behaviors and motivations.The study will help academic libraries improve their social bookmarking service.Originality/value:In spite of growing popularity of social bookmarking sites,little has been known about the social bookmarking behaviors of library users.This study investigated college students' social bookmarking behaviors and motivations,providing suggestions for academic libraries to improve their social bookmarking services.展开更多
Video-on-demand （VoD） services have become popular on the Internet in recent years. In VoD, it is challeng- ing to support the VCR functionality, especially the jumps, while maintaining a smooth streaming quality. P...Video-on-demand （VoD） services have become popular on the Internet in recent years. In VoD, it is challeng- ing to support the VCR functionality, especially the jumps, while maintaining a smooth streaming quality. Previous stud- ies propose to solve this problem by predicting the jump tar- get locations and prefetching the contents. However, through our analysis on traces from a real-world VoD service, we find that it would be fundamentally difficult to improve a viewer＇s VCR experience by simply predicting his future jumps, while ignoring the intentions behind these jumps. Instead of the prediction-based approach, in this paper, we seek to support the VCR functionality by bookmark- ing the videos. There are two key techniques in our pro- posed methodology. First, we infer and differentiate view- ers＇ intentions in VCR jumps by decomposing the inter- seek times, using an expectation-maximization （EM） algo- rithm, and combine the decomposed inter-seek times with the VCR jumps to compute a numerical interest score for each video segment. Second, based on the interest scores, we pro- pose an automated video bookrnarking algorithm. The algo- rithm employs the time-series change detection techniques of CUSUM and MB-GT, and bookmarks videos by detecting the abrupt changes on their interest score sequences. We evaluate our proposed techniques using real-world VoD traces from dozens of videos. Experimental results suggest that with our methods, viewers＇ interests within a video can be precisely extracted, and we can position bookmarks on the video＇shighlight events accurately. Our proposed video bookmark- ing methodology does not require any knowledge on video type, contents, and semantics, and can be applied on various types of videos.展开更多
基金supported by the National Youth Top-notch Talent Support Program of China
文摘Purpose:To have a better understanding of library users' social bookmarking behaviors,we conducted a survey of college students to examine how much attention they have paid to social bookmarking results,their social bookmarking motivations and behaviors on book sharing sites and in their library's OPAC,and their expectations to their library's social bookmarking service.Design/methodology/approach:A questionnaire survey was conducted to investigate social bookmarking behaviors and motivations of users of Wuhan University Library(WUL) on book sharing sites and in WUL's OPAC.A total of 700 questionnaires were distributed and357 valid questionnaires were retrieved.SPSS was used for data analysis.Findings:The results revealed that there were differences between users' social bookmarking behaviors on book sharing sites and in the Library's OPAC.Users preferred to use tags than add tags on book sharing sites.The main tagging motivation on book sharing sites was for meeting users' specific needs such as collection management and book recommendations.As for the Library,the lack of publicity and promotion of the social bookmarking service led to insufficient use of the Library's service.Due to a lack of knowledge of the social bookmarking service,users did not care about the lectures or publicity campaigns about the Library's social bookmarking service.Research limitations:Because social bookmarking was not common among WUL users,and the questionnaires could be handed out to a limited number of people,it was hard to describe users' social bookmarking behaviors in the Library's OPAC by investigating a sample of 357Library users,and therefore we only investigated users' social bookmarking behaviors on the book sharing sites.Practical implications:The survey results provide insights into library users' social bookmarking behaviors and motivations.The study will help academic libraries improve their social bookmarking service.Originality/value:In spite of growing popularity of social bookmarking sites,little has been known about the social bookmarking behaviors of library users.This study investigated college students' social bookmarking behaviors and motivations,providing suggestions for academic libraries to improve their social bookmarking services.
文摘Video-on-demand （VoD） services have become popular on the Internet in recent years. In VoD, it is challeng- ing to support the VCR functionality, especially the jumps, while maintaining a smooth streaming quality. Previous stud- ies propose to solve this problem by predicting the jump tar- get locations and prefetching the contents. However, through our analysis on traces from a real-world VoD service, we find that it would be fundamentally difficult to improve a viewer＇s VCR experience by simply predicting his future jumps, while ignoring the intentions behind these jumps. Instead of the prediction-based approach, in this paper, we seek to support the VCR functionality by bookmark- ing the videos. There are two key techniques in our pro- posed methodology. First, we infer and differentiate view- ers＇ intentions in VCR jumps by decomposing the inter- seek times, using an expectation-maximization （EM） algo- rithm, and combine the decomposed inter-seek times with the VCR jumps to compute a numerical interest score for each video segment. Second, based on the interest scores, we pro- pose an automated video bookrnarking algorithm. The algo- rithm employs the time-series change detection techniques of CUSUM and MB-GT, and bookmarks videos by detecting the abrupt changes on their interest score sequences. We evaluate our proposed techniques using real-world VoD traces from dozens of videos. Experimental results suggest that with our methods, viewers＇ interests within a video can be precisely extracted, and we can position bookmarks on the video＇shighlight events accurately. Our proposed video bookmark- ing methodology does not require any knowledge on video type, contents, and semantics, and can be applied on various types of videos.
