Browsing by Author "Tseng, Tzu-Ting"

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Car Together: Sharing Real-Time Captured Video through Vehicles on Roads
(2015)
Hu, Chih-Lin
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Wang, Shih-Kai
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Lu, Ming-Ying
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Tseng, Tzu-Ting
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Lin, Cheng-Lun
This paper presents a system and method for enabling real-time captured video sharing services among neighboring vehicles in self-organized vehicular network environments. When vehicles are equipped with image capturing and Wi-Fi modules, they are capable of establishing local wireless networks, connecting with other peers, and fetching on-line video records from neighboring peers. This service design can offer drivers a broad range of visibility that is likely influenced by front cars, road-side obstacles, or curve roads. After prototypical development and demonstration, this paper shows that the deployment of this service on vehicles is able to assist drivers in driving safety on roads.
Searching for Truss Alpha Users in Mobile Telecommunications Social Networks
(2013-01-01)
Gau, Rung-Hung
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Tsai, Sheng-Wen
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Tseng, Tzu-Ting
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電機工程學系
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Department of Electrical and Computer Engineering
In this paper, we propose a novel approach for the analysis of large-scale mobile telecommunications social networks. To search for alpha users that are essential for social marketing, we propose using both graph theory and linear algebra. In particular, we first look for all trusses in a social graph based on graph theory and then find out alpha users in the trusses based on linear algebra. While there is no proof that the adjacency matrix of a graph always has strictly positive eigenvectors, we prove that the adjacency matrix of a truss always has positive eigenvectors. The proposed approach is scalable and can be used to analyze massive networks.
Social trend tracking by time series based social tagging clustering
(2011-09-15)
Chen, Shihn-Yuarn
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Tseng, Tzu-Ting
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Ke, Hao-Ren
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Sun, Chuen-Tsai
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資訊工程學系
Social tagging is widely practiced in the Web 2.0 era. Users can annotate useful or interesting Web resources with keywords for future reference. Social tagging also facilitates sharing of Web resources. This study reviews the chronological variation of social tagging data and tracks social trends by clustering tag time series. The data corpus in this study is collected from Hemidemi.com. A tag is represented in a time series form according to its annotating Web pages. Then time series clustering is applied to group tag time series with similar patterns and trends in the same time period. Finally, the similarities between clusters in different time periods are calculated to determine which clusters have similar themes, and the trend variation of a specific tag in different time periods is also analyzed. The evaluation shows the recommendation accuracy of the proposed approach is about 75%. Besides, the case discussion also proves the proposed approach can track the social trends. (C) 2011 Elsevier Ltd. All rights reserved.