Data Mining and Visualization System Design and Development

Article Preview

Abstract:

With the rise of the network,everyday the video websites update plenty of video datas.Faced with a lot of video datas,if you only rely on the human to analyze the video datas in order to dig out the information hidden in the video room,it will take a lot of time and is difficult to achieve the desired result. This paper develops a data mining and visualization system,which visualized shows the relationship between the video datas through a network graph of nodes.Based on visualized showing the relationship between the video datas,the system provides the tool to analyze the video datas and dig out the information hidden in the video room.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 971-973)

Pages:

1444-1448

Citation:

Online since:

June 2014

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Marc Najork, Janet L. Wiener: Breadth-First Search Crawling Yields High-Quality Pages(2001). In ACM(Hong Kong): 114-118.

DOI: 10.1145/371920.371965

Google Scholar

[2] Soumen Chakrabarti, Martin van den Bergb, Byron Dom: Focused crawling: a new approach to topic-specific Web resource discovery(1999). Computer Networks 31 (1999) : 1623–1640.

DOI: 10.1016/s1389-1286(99)00052-3

Google Scholar

[3] Edwards, J., McCurley, K. S., and Tomlin, J. A.: An adaptive model for optimizing performance of an incremental web crawler(2001). In Proceedings of the Tenth Conference on World Wide Web (Hong Kong: Elsevier Science): 106–113.

DOI: 10.1145/371920.371960

Google Scholar

[4] Wu, Z., & Tseng, G.: ACTS: An automatic Chinese text segmentation system for full text retrieval(1995). 46(2), 83–96.

DOI: 10.1002/(sici)1097-4571(199503)46:2<83::aid-asi2>3.0.co;2-0

Google Scholar

[5] Meknavin, S., Charoenpornsawat, P., & Kijsirikul, B.: Feature-based Thai word segmentation (1997).

Google Scholar

[6] Christopher C. Yang and K. W. Li: A Heuristic Method Based on a Statistical Approach for Chinese Text Segmentation(2005). 56(13): 1438–1447.

Google Scholar

[7] Giridhar Kumaran and James Allan: Text Classification and Named Entities for New Event Detection(2004).

Google Scholar

[8] Yoav Freund Robert E. Schapire: A Short Introduction to Boosting, Journal of Japanese Society for Artificial Intelligence(1999). 14(5): 771-780.

Google Scholar

[9] Liu Yang: Distance Metric Learning: A Comprehensive Survey(2006).

Google Scholar

[10] Information on http: /d3js. org.

Google Scholar