Detection of Entity Mixture in Knowledge Bases Using Hierarchical Clustering-Reference-Cited by-同舟云学术

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Detection of Entity Mixture in Knowledge Bases Using Hierarchical Clustering

Published:2016 Issue: Volume: Page:288-299
ISSN:0302-9743
Container-title:Natural Language Understanding and Intelligent Applications
language:
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Author:

Xie Haihua,Lu Xiaoqing,Tang Zhi,Huang Xiaojun

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-50496-4_24

Reference18 articles.

1. Weichselbraun, A., Gindl, S., Scharl, A.: Enriching semantic knowledge bases for opinion mining in big data applications. Know. Based Syst. 69(1), 78–85 (2014)

2. Bengio, Y., Courville, A., Vincent, P.: Representation learning: a review and new perspectives. IEEE Trans. Softw. Eng. 35(8), 1798–1828 (2014)

3. Sondhi, P., Zhai, C.: Mining semi-structured online knowledge bases to answer natural language questions on community QA websites. In: Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014), pp. 341–350 (2014)

4. West, R., Gabrilovich, E., Murphy, K., Sun, S., Gupta, R., Lin, D.: Knowledge base completion via search-based question answering. In: Proceedings of the 23rd International Conference on World Wide Web (WWW 2014), pp. 515–526 (2014)

5. Chen, M., Pavalanathan, U., Jensen, S., Plale, B.: Modeling heterogeneous data resources for social-ecological research: a data-centric perspective. In: Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL 2013), pp. 309–312 (2013)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Clustering Analysis-Based Approach to Detecting Entity Mixture in Knowledge Bases;Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries;2018-05-23

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