Short text keyphrase extraction with hypergraphs-Reference-Cited by-同舟云学术

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Short text keyphrase extraction with hypergraphs

Published:2014-08-20 Issue:2 Volume:3 Page:73-87
ISSN:2192-6352
Container-title:Progress in Artificial Intelligence
language:en
Short-container-title:Prog Artif Intell

Author:

Bellaachia Abdelghani,Al-Dhelaan Mohammed

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

http://link.springer.com/content/pdf/10.1007/s13748-014-0058-1.pdf

Reference60 articles.

1. Agarwal, A., Chakrabarti, S.: Learning random walks to rank nodes in graphs. In: Proceedings of the 24th international conference on machine learning, pp. 9–16. ACM, New York, NY (2007)

2. Agarwal, A., Chakrabarti, S., Aggarwal, S.: Learning to rank networked entities. In: Proceedings of the 12th ACM SIGKDD international conference on knowledge discovery and data mining, pp. 14–23. ACM, New York, NY (2006)

3. Agarwal, S., Branson, K., Belongie, S.: Higher order learning with graphs. In: Proceedings of the 23rd international conference on machine learning, pp. 17–24. ACM, New York, NY (2006)

4. Aldous, D., Fill, J.: Reversible markov chains and random walks on graphs (2002)

5. Avin, C., Lando, Y., Lotker, Z.: Radio cover time in hyper-graphs. In: Proceedings of the 6th international workshop on foundations of mobile computing, pp. 3–12. ACM, New York, NY (2010)

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1. Sentiment diversification for short review summarization;Proceedings of the International Conference on Web Intelligence;2017-08-23

2. Domain adaptation network based on hypergraph regularized denoising autoencoder;Artificial Intelligence Review;2017-08-04

3. Graph Summarization for Hashtag Recommendation;2015 3rd International Conference on Future Internet of Things and Cloud;2015-08

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