參考文獻 |
參考文獻
中文部分
[1]. 林文羽、林熙禎,(2013),「關鍵字為基礎的多主題概念飄移學習」,TANET2013臺灣網際網路研討會-論文集
[2]. 李浩平、林熙禎,(2011),「運用NGD建立適用於使用者回饋資訊不足之文件過濾系統」,國立中央大學,碩士論文
[3]. 鄭奕駿、林熙禎,(2012),「離線搜尋Wikipedia以縮減NGD運算時間之研究」,國立中央大學,碩士論文
[4]. 鄭運剛、馬建國,(2008),“A Model of User s Interests Drift Based on Classification Model,” Journal of Information, no. 1
[5]. 蘇怡仁、溫建成、許維麟、陳岳群,(2012),「以重疊社群分析引文網路支援論文自動分類之探討」,The 8th International Conference on Knowledge Community
英文部分
[6]. Aggarwal, Charu C. and Yu, Philip S., (2006), “A Framework for Clustering Massive Text and Categorical Data Streams,” Proceedings of the SIAM Conference on Data Mining (SDM)
[7]. Brandes, Ulrik, (2001), “A faster algorithm for betweenness centrality,” Journal of Mathematical Sociology, vol. 25, pp. 163-177
[8]. Bifet, Albert, Holmes, Geoff, Pfahringer, Bernhard and Gavaldà, Ricard, (2011), “Mining Frequent Closed Graphs on Evolving Data Streams,” 17th ACM SIGKDD international conference on Knowledge discovery and data mining, pp, 591-599
[9]. Chang, H.-C. and Chiun-Chieh, H., (2005), “Using topic keyword clusters for automatic document clustering,” IEICE TRANSACTIONS on Information and Systems, vol. 88, pp. 1852-1860
[10]. Chen, P.-I. and Lin, S.-J., (2010), “Automatic keyword prediction using Google similarity distance,” Expert Systems with Applications, vol. 37, pp. 1928-1938
[11]. Chen, P.-I. and Lin, S.-J., (2011), “Word AdHoc network: using Google core distance to extract the most relevant information,” Knowledge-Based Systems, vol. 24, pp. 393-405
[12]. Cilibrasi, Rudi L. and Paul MB Vitanyi, (2007), “The google similarity distance,” IEEE Transactions on Knowledge and Data Engineering, vol. 19, no. 3, pp. 370-383.
[13]. Dietz, Laura and Dalton and Jeffrey, (2012), “Acrossdocument neighborhood expansion: UMass at TAC KBP 2012 entity linking,” Text Analysis Conference (TAC)
[14]. Dijkstra, E. W., (1959), “A note on two problems in connexion with graphs,” Numerische mathematik, vol. 1, pp. 269-271.
[15]. Farid, Dewan Md., Zhang, Li, Hossain, Alamgir, Rahman, Chowdhury Mofizur, Strachan, Rebecca, Sexton, Graham and Dahal, Keshav, (2013), “An adaptive ensemble classifier for mining concept drifting data streams,” Expert Systems with Applications, vol. 40, pp. 5895-5906
[16]. Girvan, M. and Newman, M. E., (2002), “Community structure in social and biological networks,” Proceedings of the National Academy of Sciences, vol. 99, pp. 7821-7826
[17]. Gu, Suicheng, Tan, Ying and He, Xingui, (2013), “Recentness biased learning for time series forecasting,” Information Sciences, vol. 237, pp. 29-38
[18]. Koehn, Philipp, Och, Franz Josef and Marcu, Daniel, (2003), “Statistical phrase-based translation,” Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology-Volume 1. Association for Computational Linguistics, pp. 48-54
[19]. Li, Lei, Zheng, Li, Yang, Fan and Li, Tao, (2014), “Modeling and broadening temporal user interest in personalized news recommendation,” Expert Systems with Applications, vol. 41, pp. 3168-3177
[20]. Nanas, Nikolaos, Uren, Victoria, Roeck, Anne de and Domingue, John, (2004), “Multi-topic Information Filtering with a Single User Profile,” Methods and Applications of Artificial Intelligence, vol. 3025, pp. 400-409
[21]. Tufis, D. and Mason, O., (1998), “Tagging romanian texts: a case study for qtag, a language independent probabilistic tagger,” Proceedings of the First International Conference on Language Resources and Evaluation (LREC), pp. 589-596
[22]. Wang, Hongwei and Zou, Li, (2013), “Modeling User Preference Based on Long-term and Short-term Interest,” Journal of Tongji University(Natural Science), vol. 06
[23]. Yang, Jiping, Wang, Yue and Gao, Xuesong, (2011), “User interest modeling for personalized streaming media services based on behavior analysis,” Computer Applications and Software, vol. 28, no. 8
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