Study on Keyword Search with Mutual Interests of Social Networks
碩士 === 世新大學 === 資訊管理學研究所(含碩專班) === 100 === As the booming of social network sites (SNSs), people adapt to communicate and share information via internet recently. According to great business opportunities emerging in SNSs, entrepreneurs strive to explore kinds of potential possibilities to make use...
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ndltd-TW-100SHU053960072015-10-13T21:17:10Z http://ndltd.ncl.edu.tw/handle/83653585814990076222 Study on Keyword Search with Mutual Interests of Social Networks 結合社群共同喜好之關鍵字搜尋研究 Yu-lien Hsieh 謝玉蓮 碩士 世新大學 資訊管理學研究所(含碩專班) 100 As the booming of social network sites (SNSs), people adapt to communicate and share information via internet recently. According to great business opportunities emerging in SNSs, entrepreneurs strive to explore kinds of potential possibilities to make use data collected from SNSs. For example, recently the well-known Search Engine Site, Google, has released Google+ to integrate the task of keyword search with social network. Therefore, the related web pages returned from Search Engine might be much more toward individual needs. In this paper, we propose a new method to consider the mutual interests of friends on social networks while ranking the orders of related web pages returned from search engines. A web-browsing log of 1112 users kept by InsightXplorer Ltd. is explored, and the simulation results show the proposed method could improve Google Search in page ranks and precision values (P@Ns). Yu-Chin Liu 劉育津 2012 學位論文 ; thesis 65 zh-TW |
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碩士 === 世新大學 === 資訊管理學研究所(含碩專班) === 100 === As the booming of social network sites (SNSs), people adapt to communicate and share information via internet recently. According to great business opportunities emerging in SNSs, entrepreneurs strive to explore kinds of potential possibilities to make use data collected from SNSs. For example, recently the well-known Search Engine Site, Google, has released Google+ to integrate the task of keyword search with social network. Therefore, the related web pages returned from Search Engine might be much more toward individual needs.
In this paper, we propose a new method to consider the mutual interests of friends on social networks while ranking the orders of related web pages returned from search engines. A web-browsing log of 1112 users kept by InsightXplorer Ltd. is explored, and the simulation results show the proposed method could improve Google Search in page ranks and precision values (P@Ns).
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Yu-Chin Liu |
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Yu-Chin Liu Yu-lien Hsieh 謝玉蓮 |
author |
Yu-lien Hsieh 謝玉蓮 |
spellingShingle |
Yu-lien Hsieh 謝玉蓮 Study on Keyword Search with Mutual Interests of Social Networks |
author_sort |
Yu-lien Hsieh |
title |
Study on Keyword Search with Mutual Interests of Social Networks |
title_short |
Study on Keyword Search with Mutual Interests of Social Networks |
title_full |
Study on Keyword Search with Mutual Interests of Social Networks |
title_fullStr |
Study on Keyword Search with Mutual Interests of Social Networks |
title_full_unstemmed |
Study on Keyword Search with Mutual Interests of Social Networks |
title_sort |
study on keyword search with mutual interests of social networks |
publishDate |
2012 |
url |
http://ndltd.ncl.edu.tw/handle/83653585814990076222 |
work_keys_str_mv |
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