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ALTAS: An Intelligent Text Analysis System Based on Knowledge Graphs

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10987))

Abstract

This paper presents an intelligent text analysis system, called ALTAS, to support various text analysis tasks such as statistics analysis, sentiment analysis, text classification, and text clustering. The system contains four main components: knowledge graphs, text processing, text analysis and intelligent report. First, the system has built a semantic-rich knowledge base using several knowledge graph resources. A novel text processing and analysis framework based on knowledge graphs is developed and implemented. Given a text dataset, the text processing phase will do data cleaning, word segmentation and feature extraction for it. With the extracted features, the text analysis phase allows users to select a text mining task. We have implemented the proposed novel algorithm and several typical algorithms for each task. If users select multiple algorithms for the task, the intelligent report phase will automatically generate comparison results for users. Especially, the intelligent report phase also provides users a paper summary generating function on text mining problems.

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References

  1. Yu, L., Zheng, J., Shen, W.C., et al.: BC-PDM: data mining, social network analysis and text mining system based on cloud computing. In: ACM SIGKDD, pp. 1496–1499 (2012)

    Google Scholar 

  2. Bansal, N., Koudas, N.: BlogScope: a system for online analysis of high volume text streams. In: VLDB, pp. 1410–1413 (2007)

    Google Scholar 

  3. Alpaydin, E.: Introduction to Machine Learning. MIT Press, Cambridge (2010)

    MATH  Google Scholar 

  4. Quora. https://www.quora.com/sitemap/topics

  5. Lin, K., Wu, M., Wang, X., Yang, P.: MEDLedge: a Q&A based system for constructing medical knowledge base. In: ICCSE, pp. 485–489 (2016)

    Google Scholar 

  6. Xmfish. http://www.xmfish.com/

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Acknowledgment

This work is supported by the National Natural Science Foundation of China under Grant No. 61702432, and the International Cooperation Projects of Fujian Province in China under Grant No. 2018I0016.

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Correspondence to Kunhui Lin .

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© 2018 Springer International Publishing AG, part of Springer Nature

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Wang, X., Gao, C., Cao, J., Lin, K., Du, W., Yang, Z. (2018). ALTAS: An Intelligent Text Analysis System Based on Knowledge Graphs. In: Cai, Y., Ishikawa, Y., Xu, J. (eds) Web and Big Data. APWeb-WAIM 2018. Lecture Notes in Computer Science(), vol 10987. Springer, Cham. https://doi.org/10.1007/978-3-319-96890-2_40

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  • DOI: https://doi.org/10.1007/978-3-319-96890-2_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-96889-6

  • Online ISBN: 978-3-319-96890-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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