Abstract
Nowadays contents of the web multiply everyday. However, for particular company or individual, some kind of information has higher priority. For example, among so much information on the internet, web pages containing academic papers are definitely more attractive to a researcher. And the problem lies in how to find that kind of data. Therefore we design a spider that targets only on online academic papers. Besides reserving three major parts of a traditional spider, we make some modifications on Filter and Parser so that our spider is competent enough to accomplish the mission. And the essential mechanism of recognizing and extracting expected pages primarily lies on keyword-matching and Finite State Machine Theory. After roaming on two web sites, the spider successfully collects desirable information. We can safely see from the result that in future by optimization and modification this theme-based spider may work more efficiently or even expands to other fields of interest.
This work are supported by Natural Science Foundation of China (Nos. 61472381, 61472382, 61572454 and 61174144), NOE-Micrsoft Key Laboratory of Multimedia Computing and Communication Foundation, Anhui Province Key Laboratory of Software in Computing and Communication.
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Appendix: URLs of Search Engines
Appendix: URLs of Search Engines
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Google: http://www.google.cn
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Baidu: http://www.baidu.com
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Science Paper Online: http://www.paper.edu.cn
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Yin, P., Shao, Q., Wang, X., Wang, W., Miao, F., Shao, C. (2017). Theme-Based Spider for Academic Paper. In: Yue, D., Peng, C., Du, D., Zhang, T., Zheng, M., Han, Q. (eds) Intelligent Computing, Networked Control, and Their Engineering Applications. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 762. Springer, Singapore. https://doi.org/10.1007/978-981-10-6373-2_23
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DOI: https://doi.org/10.1007/978-981-10-6373-2_23
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