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題名 智慧型手機的使用者行為模式分析
Behavior Analysis Based on Smart-phone User Logs
作者 許志毓
Hsu, Chih Yu
貢獻者 廖文宏
Liao, Wen Hung
許志毓
Hsu, Chih Yu
關鍵詞 行為模式
使用習慣
特徵相似度
序列比對
behavior pattern
app usage
feature similarity
sequence matching
日期 2013
上傳時間 2-一月-2014 14:06:56 (UTC+8)
摘要 通訊技術的演化與智慧型手機的普及，改變了人際溝通的方式與手機的應用情境，在此變動快速的行動運算時代，欲研究探討使用者的行為模式，必須建立一個包含硬體、軟體與使用者社群的實驗平台，以量化的數據補強質性的觀察，準此，本論文將以現有之平台為基礎，強化其功能與易用性，方便其他研究者觀察資料的概況，並擷取符合某些條件之資料，此外，我們採用3-gram之應用程式序列，作為行為模式(behavior pattern)之特徵定義，配合不同的應用程式被使用之頻率，在相似度比較上進行不同比重的加權，根據實驗結果，可大致對使用者進行初步的分類，亦可利用此指標，針對已分類過的使用者更進一步探討之間的歧異程度。
The rapid evolution of information technology and prevalence of smart-phones have changed the way people communicate. To effectively observe and investigate user behavior in this new era of mobile computing, an experimental platform that consists of hardware devices, software applications and user groups is essential. In this thesis, we enhance and extend the functions of a user log collection and analysis system to facilitate quick overview of the recorded data and allow flexible query/extraction of desired data segments for further processing. In addition, we employ 3-gram app log sequence as the main feature to characterize user behavior. A similarity measure that takes into account the relative app usage frequency has been defined to compare and classify users and their usage patterns. Experimental results indicate that this measure can effectively distinguish users of different traits given enough time period of observation.
參考文獻 [1] Po-Ming Chen, Hui-Yin Wu, Chih-Yu Hsu, Wen-Hung Liao, Tsai-Yen Li Logging and analyzing long-term mobile user behaviors, International Journal of Electronic Commerce Studies, 2012.
[2] N. Eagle, and A. Pentland, Reality mining: sensing complex social systems. Personal Ubiquitous Computing, 10(4), 255-268, 2006.
[3] I. Pramudiono, T. Shintani, K. Takahashi, and M. Kitsuregawa: User Behavior Analysis of Location Aware Search Engine. Mobile Data Management, 139-145, 2002.
[4] R. A. Baeza-Yates. Applications of web query mining. ECIR, 7-22, 2005.
[5] N. Ducheneaut, N. Yee, E. Nickell, and R. J. Moore, The life and death of online gaming communities: a look at guilds in world of warcraft. Proceedings of the SIGCHI conference on Human factors in computing systems, 2007.
[6] J. Kort, and H. de Poot, Usage Analysis: Combining Logging and Qualitative Methods. Proceedings of the 2005 CHI Conference on Human Factors in Computing Systems (Extended Abstracts), Vienna: ACM Press, 2121-2122, 2005.
[7] D. M. Hilbert, and D. F. Redmiles, Extracting Usability Information from User Interface Events. ACM Computing Surveys 2000, Vol. 32, No.4, 384-421, 2000.
[8] Naaman, Mor, Rahul Nair, and Vlad Kaplun. "Photos on the go: a mobile application case study." Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2008.
[9] Lee, Alison. "Exploiting context for mobile user experience." Position Papers for the 1st Workshop on Semantic Models for Adaptive Interactive Systems (SEMAIS 2010). 2010.
[10] Baeza-Yates, Roberto. "Web usage mining in search engines." Web mining: applications and techniques (2004): 307-321.
描述 碩士
國立政治大學
資訊科學學系
100753028
102
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0100753028
資料類型 thesis
dc.contributor.advisor 廖文宏zh_TW
dc.contributor.advisor Liao, Wen Hungen_US
dc.contributor.author (作者) 許志毓zh_TW
dc.contributor.author (作者) Hsu, Chih Yuen_US
dc.creator (作者) 許志毓zh_TW
dc.creator (作者) Hsu, Chih Yuen_US
dc.date (日期) 2013en_US
dc.date.accessioned 2-一月-2014 14:06:56 (UTC+8)-
dc.date.available 2-一月-2014 14:06:56 (UTC+8)-
dc.date.issued (上傳時間) 2-一月-2014 14:06:56 (UTC+8)-
dc.identifier (其他 識別碼) G0100753028en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/63215-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學學系zh_TW
dc.description (描述) 100753028zh_TW
dc.description (描述) 102zh_TW
dc.description.abstract (摘要) 通訊技術的演化與智慧型手機的普及，改變了人際溝通的方式與手機的應用情境，在此變動快速的行動運算時代，欲研究探討使用者的行為模式，必須建立一個包含硬體、軟體與使用者社群的實驗平台，以量化的數據補強質性的觀察，準此，本論文將以現有之平台為基礎，強化其功能與易用性，方便其他研究者觀察資料的概況，並擷取符合某些條件之資料，此外，我們採用3-gram之應用程式序列，作為行為模式(behavior pattern)之特徵定義，配合不同的應用程式被使用之頻率，在相似度比較上進行不同比重的加權，根據實驗結果，可大致對使用者進行初步的分類，亦可利用此指標，針對已分類過的使用者更進一步探討之間的歧異程度。zh_TW
dc.description.abstract (摘要) The rapid evolution of information technology and prevalence of smart-phones have changed the way people communicate. To effectively observe and investigate user behavior in this new era of mobile computing, an experimental platform that consists of hardware devices, software applications and user groups is essential. In this thesis, we enhance and extend the functions of a user log collection and analysis system to facilitate quick overview of the recorded data and allow flexible query/extraction of desired data segments for further processing. In addition, we employ 3-gram app log sequence as the main feature to characterize user behavior. A similarity measure that takes into account the relative app usage frequency has been defined to compare and classify users and their usage patterns. Experimental results indicate that this measure can effectively distinguish users of different traits given enough time period of observation.en_US
dc.description.tableofcontents 1. 引言 6
2. 相關研究 11
3. 資料蒐集平台介紹 13
3.1 User 15
3.2 Log Collector Service 15
3.2.1. Service dataflow 16
3.2.2. Log Table in Remote Database 17
3.2.3. Log Collector Service Limited 18
3.3 Log Monitor Platform 19
3.3.1. Log Charting Service 19
3.3.2. Log Query and List Website 20
3.3.3. Log Real-time Monitor 22
4. 研究方法 23
4.1. 取標準差變異數來代表資料的特徵 27
4.2. 定義使用者特殊的行為模式作為特徵 29
5. 實驗結果與討論 42
5.1 Log Charting Service 42
5.2 Log Query Service 45
5.3 Log Real-time Monitor 47
5.4 特徵分析 52
6. 結論 69
7. 參考文獻 71		zh_TW
dc.format.extent 6767509 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0100753028en_US
dc.subject (關鍵詞) 行為模式zh_TW
dc.subject (關鍵詞) 使用習慣zh_TW
dc.subject (關鍵詞) 特徵相似度zh_TW
dc.subject (關鍵詞) 序列比對zh_TW
dc.subject (關鍵詞) behavior patternen_US
dc.subject (關鍵詞) app usageen_US
dc.subject (關鍵詞) feature similarityen_US
dc.subject (關鍵詞) sequence matchingen_US
dc.title (題名) 智慧型手機的使用者行為模式分析zh_TW
dc.title (題名) Behavior Analysis Based on Smart-phone User Logsen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) [1] Po-Ming Chen, Hui-Yin Wu, Chih-Yu Hsu, Wen-Hung Liao, Tsai-Yen Li Logging and analyzing long-term mobile user behaviors, International Journal of Electronic Commerce Studies, 2012.
[2] N. Eagle, and A. Pentland, Reality mining: sensing complex social systems. Personal Ubiquitous Computing, 10(4), 255-268, 2006.
[3] I. Pramudiono, T. Shintani, K. Takahashi, and M. Kitsuregawa: User Behavior Analysis of Location Aware Search Engine. Mobile Data Management, 139-145, 2002.
[4] R. A. Baeza-Yates. Applications of web query mining. ECIR, 7-22, 2005.
[5] N. Ducheneaut, N. Yee, E. Nickell, and R. J. Moore, The life and death of online gaming communities: a look at guilds in world of warcraft. Proceedings of the SIGCHI conference on Human factors in computing systems, 2007.
[6] J. Kort, and H. de Poot, Usage Analysis: Combining Logging and Qualitative Methods. Proceedings of the 2005 CHI Conference on Human Factors in Computing Systems (Extended Abstracts), Vienna: ACM Press, 2121-2122, 2005.
[7] D. M. Hilbert, and D. F. Redmiles, Extracting Usability Information from User Interface Events. ACM Computing Surveys 2000, Vol. 32, No.4, 384-421, 2000.
[8] Naaman, Mor, Rahul Nair, and Vlad Kaplun. "Photos on the go: a mobile application case study." Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2008.
[9] Lee, Alison. "Exploiting context for mobile user experience." Position Papers for the 1st Workshop on Semantic Models for Adaptive Interactive Systems (SEMAIS 2010). 2010.
[10] Baeza-Yates, Roberto. "Web usage mining in search engines." Web mining: applications and techniques (2004): 307-321.		zh_TW