Extended Clickstream: an analysis of the missing user behaviors in the Clickstream

碩士 === 國立中央大學 === 資訊工程學系 === 107 === Nowadays, people often use clickstream to represent the behavior of online users. However, we found that clickstream only represents part of users' browsing behaviors. For instance, clickstream does not include tab switching and browser window switching. We...

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Main Authors: Ting-Rui Chen, 陳廷睿
Other Authors: Hung-Hsuan Chen
Format: Others
Language:en_US
Published: 2019
Online Access:http://ndltd.ncl.edu.tw/handle/9nrd3r
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spelling ndltd-TW-107NCU053920672019-10-22T05:28:12Z http://ndltd.ncl.edu.tw/handle/9nrd3r Extended Clickstream: an analysis of the missing user behaviors in the Clickstream 擴展點擊流:分析點擊流中缺少的使用者行為 Ting-Rui Chen 陳廷睿 碩士 國立中央大學 資訊工程學系 107 Nowadays, people often use clickstream to represent the behavior of online users. However, we found that clickstream only represents part of users' browsing behaviors. For instance, clickstream does not include tab switching and browser window switching. We collect these kinds of behaviors and named as ``extended clickstream". This thesis builds a service to capture both of clickstream and extended clickstream, also provides an analysis of the differences between above. We use a Multi-Task learning model with GRU components to perform multi-objective predictions of ``what kind of website the user will go next time" and ``how long the interval of clicks will be" for the time series of clickstreams and extended clickstreams. Our experimental results show that combining clickstream and extended clickstream can improve the prediction performance. In addition, this article finds that the clickstream will record unintended clicks due to the operation mechanism of certain websites. Moreover, we can differentiate the single user from several devices by combining the clickstream and extended clickstream. Hung-Hsuan Chen 陳弘軒 2019 學位論文 ; thesis 62 en_US
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description 碩士 === 國立中央大學 === 資訊工程學系 === 107 === Nowadays, people often use clickstream to represent the behavior of online users. However, we found that clickstream only represents part of users' browsing behaviors. For instance, clickstream does not include tab switching and browser window switching. We collect these kinds of behaviors and named as ``extended clickstream". This thesis builds a service to capture both of clickstream and extended clickstream, also provides an analysis of the differences between above. We use a Multi-Task learning model with GRU components to perform multi-objective predictions of ``what kind of website the user will go next time" and ``how long the interval of clicks will be" for the time series of clickstreams and extended clickstreams. Our experimental results show that combining clickstream and extended clickstream can improve the prediction performance. In addition, this article finds that the clickstream will record unintended clicks due to the operation mechanism of certain websites. Moreover, we can differentiate the single user from several devices by combining the clickstream and extended clickstream.
author2 Hung-Hsuan Chen
author_facet Hung-Hsuan Chen
Ting-Rui Chen
陳廷睿
author Ting-Rui Chen
陳廷睿
spellingShingle Ting-Rui Chen
陳廷睿
Extended Clickstream: an analysis of the missing user behaviors in the Clickstream
author_sort Ting-Rui Chen
title Extended Clickstream: an analysis of the missing user behaviors in the Clickstream
title_short Extended Clickstream: an analysis of the missing user behaviors in the Clickstream
title_full Extended Clickstream: an analysis of the missing user behaviors in the Clickstream
title_fullStr Extended Clickstream: an analysis of the missing user behaviors in the Clickstream
title_full_unstemmed Extended Clickstream: an analysis of the missing user behaviors in the Clickstream
title_sort extended clickstream: an analysis of the missing user behaviors in the clickstream
publishDate 2019
url http://ndltd.ncl.edu.tw/handle/9nrd3r
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