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2019 | OriginalPaper | Chapter

Event-Oriented Keyphrase Extraction Based on Bi-clustering Model

Authors : Lin Zhao, Liangjun Zang, Longtao Huang, Jizhong Han, Songlin Hu

Published in: Computational Science – ICCS 2019

Publisher: Springer International Publishing

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Abstract

Keyphrase extraction, as a basis for many natural language processing and information retrieval tasks, can help people efficiently discover their interested information from vast streams of online documents. Previous methods are mostly proposed in general purpose, where keyphrases that represent the main topics are extracted. However, such keyphrases can hardly distinguish events from massive streams of long text documents that share similar topics and contain highly redundant information. In this paper, we address the task of keyphrase extraction for event-oriented retrieval. We propose a novel bi-clustering model for clustering the documents and keyphrases simultaneously. The model consequently makes the extracted keyphrases more specific and related to the event. We conduct a series of experiments on a real-world dataset. The experimental results demonstrate the better performance of our approach than other unsupervised approaches.

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Chung, J., Gülçehre, Ç., Cho, K., Bengio, Y.: Empirical evaluation of gated recurrent neural networks on sequence modeling. CoRR abs/1412.3555 (2014)

Dai, Z., Xiong, C., Callan, J.P., Liu, Z.: Convolutional neural networks for soft-matching n-grams in ad-hoc search. In: WSDM (2018)

Dehghani, M., Zamani, H., Severyn, A., Kamps, J., Croft, W.B.: Neural ranking models with weak supervision. In: SIGIR (2017)

Dhillon, I.S.: Co-clustering documents and words using bipartite spectral graph partitioning. In: KDD (2001)

Ding, Z., Zhang, Q., Huang, X.: Keyphrase extraction from online news using binary integer programming. In: IJCNLP (2011)

Farzindar, A., Khreich, W.: A survey of techniques for event detection in twitter. Comput. Intell. 31, 132–164 (2015)MathSciNetCrossRef

Feng, X., Huang, L., Tang, D., Ji, H., Qin, B., Liu, T.: A language-independent neural network for event detection. Sci. China Inf. Sci. 61, 1–12 (2016)

Frank, E., Paynter, G.W., Witten, I.H., Gutwin, C., et al.: Domain-specific keyphrase extraction. In: Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, pp. 668–673. Morgan Kaufmann Publishers (1999)

Guo, J., Fan, Y., Ai, Q., Croft, W.B.: A deep relevance matching model for ad-hoc retrieval. In: CIKM (2016)

10.

Hasan, K.S., Ng, V.: Automatic keyphrase extraction: a survey of the state of the art. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014) (2014)

11.

Hu, B., Lu, Z., Li, H., Chen, Q.: Convolutional neural network architectures for matching natural language sentences. In: NIPS (2014)

12.

Huang, C., Tian, Y., Zhou, Z., Ling, C.X., Huang, T.: Keyphrase extraction using semantic networks structure analysis. In: Sixth International Conference on Data Mining (ICDM 2006), pp. 275–284 (2006)

13.

Huang, P.S., He, X., Gao, J., Deng, L., Acero, A., Heck, L.P.: Learning deep structured semantic models for web search using click through data. In: CIKM (2013)

14.

Hulth, A.: Improved automatic keyword extraction given more linguistic knowledge. In: Proceedings of the 2003 Conference on Empirical Methods in NLP, pp. 216–223 (2003)

15.

Joorabchi, A., Mahdi, A.E.: Automatic keyphrase annotation of scientific documents using wikipedia and genetic algorithms. J. Inf. Sci. 39, 410–426 (2013)CrossRef

16.

Kalchbrenner, N., Grefenstette, E., Blunsom, P.: A convolutional neural network for modelling sentences. In: ACL (2014)

17.

Kim, J., Xue, X., Croft, W.B.: A probabilistic retrieval model for semistructured data. In: ECIR, pp. 228–239 (2009)

18.

Liu, Z., Huang, W., Zheng, Y., Sun, M.: Automatic keyphrase extraction via topic decomposition. In: EMNLP (2010)

19.

Liu, Z., Li, P., Zheng, Y., Sun, M.: Clustering to find exemplar terms for keyphrase extraction. In: EMNLP, pp. 257–266 (2009)

20.

Lu, Z., Li, H.: A deep architecture for matching short texts. In: Advances in Neural Information Processing Systems, pp. 1367–1375 (2013)

21.

Manning, C.D., Raghavan, P., Schütze, H.: Introduction to information retrieval (2008)

22.

Mihalcea, R., Tarau, P.: TextRank: bringing order into text. In: EMNLP (2004)

23.

Nikolaev, F., Kotov, A., Zhiltsov, N.: Parameterized fielded term dependence models for ad-hoc entity retrieval from knowledge graph. In: SIGIR (2016)

24.

Ogilvie, P., Callan, J.P.: Combining document representations for known-item search. In: SIGIR (2003)

25.

Onal, K.D., Altingövde, I.S., Senkul, P., de Rijke, M.: Getting started with neural models for semantic matching in web search. CoRR abs/1611.03305 (2016)

26.

Robertson, S.E., Zaragoza, H., Taylor, M.J.: Simple BM25 extension to multiple weighted fields. In: CIKM (2004)

27.

Shen, Y., He, X., Gao, J., Deng, L., Mesnil, G.: A latent semantic model with convolutional-pooling structure for information retrieval. In: CIKM (2014)

28.

Shi, T., Jiao, S., Hou, J., Li, M.: Improving keyphrase extraction using wikipedia semantics. In: 2008 Second International Symposium on Intelligent Information Technology Application, vol. 2, pp. 42–46 (2008)

29.

Shi, W., Zheng, W., Yu, J.X., Cheng, H., Zou, L.: Keyphrase extraction using knowledge graphs. In: Chen, L., Jensen, C.S., Shahabi, C., Yang, X., Lian, X. (eds.) APWeb-WAIM 2017, Part I. LNCS, vol. 10366, pp. 132–148. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-63579-8_11CrossRef

30.

Tomokiyo, T., Hurst, M.: A language model approach to keyphrase extraction. In: Proceedings of ACL Workshop on Multiword Expressions, pp. 33–40 (2003)

31.

Tu, W., Cheung, D.W.L., Mamoulis, N., Yang, M., Lu, Z.: Real-time detection and sorting of news on microblogging platforms. In: PACLIC (2015)

32.

Turney, P.D.: Learning algorithms for keyphrase extraction. Inf. Retr. 2, 303–336 (2000)CrossRef

33.

Wan, X., Xiao, J.: Exploiting neighborhood knowledge for single document summarization and keyphrase extraction. ACM Trans. Inf. Syst. 28, 8:1–8:34 (2010)CrossRef

34.

Wan, X., Yang, J., Xiao, J.: Towards an iterative reinforcement approach for simultaneous document summarization and keyword extraction. In: ACL (2007)

35.

Xiong, C., Dai, Z., Callan, J.P., Liu, Z., Power, R.: End-to-end neural ad-hoc ranking with kernel pooling. In: SIGIR (2017)

36.

Yang, L., Ai, Q., Guo, J., Croft, W.B.: aNMM: ranking short answer texts with attention-based neural matching model. In: CIKM (2016)

37.

Yang, M., Cui, T., Tu, W.: Ordering-sensitive and semantic-aware topic modeling. In: AAAI (2015)

38.

Zhiltsov, N., Kotov, A., Nikolaev, F.: Fielded sequential dependence model for ad-hoc entity retrieval in the web of data. In: SIGIR (2015)

39.

Zhu, J., Xu, C., Li, Z., Fung, G.P.C., Lin, X., Huang, J., Huang, C.: An examination of on-line machine learning approaches for pseudo-random generated data. Cluster Comput. 19, 1309–1321 (2016)CrossRef

Title: Event-Oriented Keyphrase Extraction Based on Bi-clustering Model
Authors: Lin Zhao
Liangjun Zang
Longtao Huang
Jizhong Han
Songlin Hu
Publisher: Springer International Publishing
Book: Computational Science – ICCS 2019
Print ISBN: 978-3-030-22749-4

Electronic ISBN: 978-3-030-22750-0

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-22750-0_16

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