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題名：根據Frequent Itemsets的變化來分析網路使用者需求趨勢--以104家教網為例
書刊名：管理資訊計算
作者：施明毅／黃紹榕
作者(外文)：Shih, Ming-yi／Huang, Shao-rong
出版日期：2017
卷期：6:特刊1
頁次：頁161-170
主題關鍵詞：資料探勘；頻繁項目集；Data mining；Emerging pattern；Frequent itemsets；FP-Growth
原始連結：連回原系統網址new window
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  • 點閱點閱:12
對一個成功的網站管理者來說，了解網路使用者的使用趨勢是一個重要的工作。藉由了解使用者的趨勢變化，可以讓網站管理者制定出更有效率的策略，並提供更好的服務。資料探勘在現今網路時代，已經變成一項重要技術來挖掘這些資訊。在本文中，我們從兩段不同的時間軸中，收集網路使用者對此網站輸入的資料，並利用FP-Growth演算法分別找出其Frequent itemsets，再根據觀察不同時期Frequent itemsets的變化來定義emerging pattern、perished pattern和persistent pattern，並用這三種patterns來分析網路使用者的使用趨勢。在本文中，我們使用104家教網－一個幫學生和教師找家教配對的網站做為資料來源，並利用此方法進行分析，來找出其需求的變化。
Understanding the trends of Web users behavior is an important factor for running a successful website. Owners or adminstrators of websites need to make efficient marketing strategies and provide better services according to the change of users hehaviors. Data mining has become a significant tool to explore such kinds of information in the Internet age. In this paper, FP-Growth algorithm was applied to discover frequent itermsets on cllected data at different periods. Three types of changes for frequent itemsets (i.e., emerging pattern, perished pattern and persistent pattern) were defined to observe the behaviors of Web users. Among the results that data were collected from 104 tutoring Web site, we showed the charactertics of changes of Web users behaviors by analyzing these derived patterns.
期刊論文
1.Song, H. S.、Kim, J. K.、Kim, S. H.(2001)。Mining the change of customer behavior in an internet shopping mall。Expert Systems with Applications，21(3)，157-168。  new window
2.Fan, H.、Ramamohanarao, K.(2006)。Fast discovery and the generalization of strong jumping emerging patterns for building compact and accurate classifiers。IEEE Transactions Knowledge and Data Engineering，18(6)，721-737。  new window
3.Ahmed, K.、Emran, A. A.、Jesmin, T.、Mukti, R. F.、Rahman, M. Z.、Ahmed, F.(2013)。Early Detection of Lung Cancer Risk Using Data Mining。Asian Pacific journal of cancer prevention，14(1)，595-598。  new window
4.Glatz, E.、Mavromatidis, S.、Ager, B.、Dimitropoulos, X.(2014)。Visualizing big network traffic data using frequent pattern mining and hypergraphs。Computing，96(1)，27-38。  new window
5.García-Borroto, M.、Martínez-Trinidad, J. F.、Carrasco-Ochoa, J. A.(2014)。A survey of emerging patterns for supervised classification。Artificial Intelligence Review，42(4)，705-721。  new window
6.Nori, F.、Deypir, M.、Sadreddini, M. H.(2013)。A sliding window based algorithm for frequent closed itemset mining over data streams。Journal of Systems and Software，86(3)，615-623。  new window
7.Li, J.、Dong, G.、Ramamohanarao, K.(2001)。Making use of the most expressive jumping emerging patterns for classification。Knowledge and Information Systems，3(2)，1-29。  new window
8.Abd-Elmegid, Laila A.、El-Sharkawi, Mohamed E.(2010)。Vertical Mining of Frequent Patterns from Uncertain Data。Computer and Information Science，3(2)，171-179。  new window
會議論文
1.Dong, G.、Li, J.(1999)。Efficient mining of emerging patterns: discovering trends and differences。The Fifth ACM Sigkdd International Conference on Knowledge Discovery and Data Mining，(會議日期: 1999/08/15-08/18)。San Diego, California。43-52。  new window
2.Bailey, J.(2002)。Fast algorithms for mining Emerging Patterns。The 6th European Conference on Principles of Data Mining and Knowledge Discovery，39-50。  new window
3.Jiang, F.、Leung, C. K.、Zhang, H.(2016)。B-mine: Frequent Pattern Mining and Its Application to Knowledge Discovery from Social Networks。18th Asia-Pacific Web Conference。  new window
4.Han, J.、Dong, G.、Yin, Y.(1999)。Efficient mining of partial periodic patterns in time series database。The Fifteenth International Conference on Data Engineering，106-115。  new window
5.Li, J.、Ramamohanarao, K.、Dong, G.(2000)。The space of jumping emerging patterns and its incremental maintenance algorithms。17th international conference on machine learning。  new window
6.Zhang, X.、Dong, G.、Ramamohanarao, K.(2000)。Information-based classification by aggregating emerging patterns。The Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents，48-53。  new window
7.Wang, Z.、Fan, H.、Ramamohanarao, K.(2004)。Exploiting maximal emerging patterns for classification。The 17th Australian joint conference on Advances in Artificial Intelligence，1062-1068。  new window
8.Han, J.、Pei, J.、Yin, Y.(2000)。Mining frequent patterns without candidate generation。The 2000 ACM SIGMOD International Conference on Management of Data。ACM。1-12。  new window
9.Agrawal, R.、Srikant, R.(1994)。Fast algorithms for mining association rules in large databases。The 20th International Conference on Very Large Data Bases。Morgan Kaufmann。487-499。  new window
圖書論文
1.Zimek, A.、Assent, I.(2014)。Frequent Pattern Mining Algorithms for Data Clustering。Frequent Pattern Mining。  new window
 
 
 
 
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