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Keyphrase Extraction in Scholarly Digital Library Search Engines

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Web Services – ICWS 2020 (ICWS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12406))

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Abstract

Scholarly digital libraries provide access to scientific publications and comprise useful resources for researchers who search for literature on specific subject areas. CiteSeerX is an example of such a digital library search engine that provides access to more than 10 million academic documents and has nearly one million users and three million hits per day. Artificial Intelligence (AI) technologies are used in many components of CiteSeerX including Web crawling, document ingestion, and metadata extraction. CiteSeerX also uses an unsupervised algorithm called noun phrase chunking (NP-Chunking) to extract keyphrases out of documents. However, often NP-Chunking extracts many unimportant noun phrases. In this paper, we investigate and contrast three supervised keyphrase extraction models to explore their deployment in CiteSeerX for extracting high quality keyphrases. To perform user evaluations on the keyphrases predicted by different models, we integrate a voting interface into CiteSeerX. We show the development and deployment of the keyphrase extraction models and the maintenance requirements.

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Notes

  1. 1.

    We have used NLP Stanford part of speech tagger.

References

  1. Grobid. https://github.com/kermitt2/grobid (2008–2020)

  2. Abu-Jbara, A., Radev, D.: Coherent citation-based summarization of scientific papers. In: ACL: HLT, pp. 500–509 (2011)

    Google Scholar 

  3. Adar, E., Datta, S.: Building a scientific concept hierarchy database (schbase). In: ACL, pp. 606–615 (2015)

    Google Scholar 

  4. Alzaidy, R., Caragea, C., Giles, C.L.: Bi-lstm-crf sequence labeling for keyphrase extraction from scholarly documents. In: WWW, pp. 2551–2557. ACM (2019)

    Google Scholar 

  5. Augenstein, I., Das, M., Riedel, S., Vikraman, L., McCallum, A.: Semeval 2017 task 10: Scienceie-extracting keyphrases and relations from scientific publications. arXiv preprint arXiv:1704.02853 (2017)

  6. Barker, K., Cornacchia, N.: Using noun phrase heads to extract document keyphrases. In: Hamilton, H.J. (ed.) AI 2000. LNCS (LNAI), vol. 1822, pp. 40–52. Springer, Heidelberg (2000). https://doi.org/10.1007/3-540-45486-1_4

    Chapter  Google Scholar 

  7. Blank, I., Rokach, L., Shani, G.: Leveraging the citation graph to recommend keywords. In: RecSys, pp. 359–362 (2013)

    Google Scholar 

  8. Bulgarov, F., Caragea, C.: A comparison of supervised keyphrase extraction models. In: WWW, pp. 13–14 (2015)

    Google Scholar 

  9. Caragea, C., Bulgarov, F., Godea, A., Gollapalli, S.D.: Citation-enhanced keyphrase extraction from research papers: a supervised approach. In: EMNLP (2014)

    Google Scholar 

  10. Caragea, C., Bulgarov, F.A., Godea, A., Gollapalli, S.D.: Citation-enhanced keyphrase extraction from research papers: a supervised approach. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014, 25–29 October 2014, Doha, Qatar, A meeting of SIGDAT, a Special Interest Group of the ACL, pp. 1435–1446 (2014) http://aclweb.org/anthology/D/D14/D14-1150.pdf

  11. Caragea, C., Wu, J., Gollapalli, S.D., Giles, C.L.: Document type classification in online digital libraries. In: Twenty-Eighth IAAI Conference (2016)

    Google Scholar 

  12. Chen, H.H., Treeratpituk, P., Mitra, P., Giles, C.L.: Csseer: an expert recommendation system based on citeseerx. In: JCDL, pp. 381–382 (2013)

    Google Scholar 

  13. Councill, I., Giles, C.L., Kan, M.Y.: ParsCit: an open-source CRF reference string parsing package. LREC 8, 661–667 (2008)

    Google Scholar 

  14. El-Beltagy, S.R., Rafea, A.: Kp-miner: participation in semeval-2. In: SemEval, pp. 190–193 (2010)

    Google Scholar 

  15. Florescu, C., Caragea, C.: Positionrank: an unsupervised approach to keyphrase extraction from scholarly documents. In: ACL, pp. 1105–1115 (2017)

    Google Scholar 

  16. Frank, E., Paynter, G.W., Witten, I.H., Gutwin, C., Nevill-Manning, C.G.: Domain-specific keyphrase extraction. In: IJCAI, pp. 668–673 (1999)

    Google Scholar 

  17. Giles, C.L., Bollacker, K.D., Lawrence, S.: Citeseer: an automatic citation indexing system. In: JCDL, pp. 89–98 (1998)

    Google Scholar 

  18. Gollapalli, S.D., Caragea, C.: Extracting keyphrases from research papers using citation networks. In: AAAI, pp. 1629–1635 (2014)

    Google Scholar 

  19. Gollapalli, S.D., Li, X.L., Yang, P.: Incorporating expert knowledge into keyphrase extraction. In: AAAI, pp. 3180–3187 (2017)

    Google Scholar 

  20. Grineva, M., Grinev, M., Lizorkin, D.: Extracting key terms from noisy and multitheme documents. In: WWW, pp. 661–670 (2009)

    Google Scholar 

  21. Hall, D., Jurafsky, D., Manning, C.D.: Studying the history of ideas using topic models. In: EMNLP, pp. 363–371 (2008)

    Google Scholar 

  22. Hammouda, K.M., Matute, D.N., Kamel, M.S.: CorePhrase: keyphrase extraction for document clustering. In: Perner, P., Imiya, A. (eds.) MLDM 2005. LNCS (LNAI), vol. 3587, pp. 265–274. Springer, Heidelberg (2005). https://doi.org/10.1007/11510888_26

    Chapter  Google Scholar 

  23. Han, H., Giles, C.L., Manavoglu, E., Zha, H., Zhang, Z., Fox, E.A.: Automatic document metadata extraction using support vector machines. In: JCDL, pp. 37–48. IEEE (2003)

    Google Scholar 

  24. Hasan, K.S., Ng, V.: Conundrums in unsupervised keyphrase extraction: making sense of the state-of-the-art. In: COLING, pp. 365–373 (2010)

    Google Scholar 

  25. Hasan, K.S., Ng, V.: Automatic keyphrase extraction: a survey of the state of the art. In: ACL, pp. 1262–1273, June 2014

    Google Scholar 

  26. Hong, K., Jeon, H., Jeon, C.: Personalized research paper recommendation system using keyword extraction based on userprofile. In: Journal of Convergence Information Technology (JCIT) (2013)

    Google Scholar 

  27. Hulth, A.: Improved automatic keyword extraction given more linguistic knowledge. In: EMNLP (2003)

    Google Scholar 

  28. Jurgens, D., Kumar, S., Hoover, R., McFarland, D., Jurafsky, D.: Measuring the evolution of a scientific field through citation frames. TACL 6, 391–406 (2018)

    Article  Google Scholar 

  29. Khabsa, M., Giles, C.L.: The number of scholarly documents on the public web. PLoS One 9(5), 25 (2014)

    Google Scholar 

  30. Larsen, P., Von Ins, M.: The rate of growth in scientific publication and the decline in coverage provided by science citation index. Scientometrics 84(3), 575–603 (2010)

    Article  Google Scholar 

  31. Liu, Z., Huang, W., Zheng, Y., Sun, M.: Automatic keyphrase extraction via topic decomposition. In: EMNLP, pp. 366–376 (2010)

    Google Scholar 

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

    Google Scholar 

  33. Lopez, P., Romary, L.: Humb: automatic key term extraction from scientific articles in grobid. In: SemEval, pp. 248–251 (2010)

    Google Scholar 

  34. Mahata, D., Kuriakose, J., Shah, R.R., Zimmermann, R.: Key2vec: automatic ranked keyphrase extraction from scientific articles using phrase embeddings. In: NAACL, pp. 634–639 (2018)

    Google Scholar 

  35. Medelyan, O., Frank, E., Witten, I.H.: Human-competitive tagging using automatic keyphrase extraction. In: EMNLP, pp. 1318–1327 (2009)

    Google Scholar 

  36. Mihalcea, R., Tarau, P.: Textrank: bringing order into texts. In: EMNLP (2004)

    Google Scholar 

  37. Nguyen, T.D., Kan, M.-Y.: Keyphrase extraction in scientific publications. In: Goh, D.H.-L., Cao, T.H., Sølvberg, I.T., Rasmussen, E. (eds.) ICADL 2007. LNCS, vol. 4822, pp. 317–326. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-77094-7_41

    Chapter  Google Scholar 

  38. Orduña-Malea, E., Ayllón, J.M., Martín-Martín, A., López-Cózar, E.D.: Methods for estimating the size of google scholar. Scientometrics 104(3), 931–949 (2015)

    Article  Google Scholar 

  39. Patel, K., Caragea, C.: Exploring word embeddings in CRF-based keyphrase extraction from research papers. In: K-CAP, pp. 37–44. ACM (2019)

    Google Scholar 

  40. Qazvinian, V., Radev, D.R.: Scientific paper summarization using citation summary networks. In: COLING. pp. 689–696, Manchester, United Kingdom (2008)

    Google Scholar 

  41. Qazvinian, V., Radev, D.R., Özgür, A.: Citation summarization through keyphrase extraction. In: COLING, pp. 895–903 (2010)

    Google Scholar 

  42. Ritchie, A., Teufel, S., Robertson, S.: How to find better index terms through citations. In: CLIIR, pp. 25–32 (2006)

    Google Scholar 

  43. Sefid, A., et al.: Cleaning noisy and heterogeneous metadata for record linking across scholarly big datasets. In: The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019, pp. 9601–9606 (2019)

    Google Scholar 

  44. Sinha, A., et al.: An overview of microsoft academic service (mas) and applications. In: WWW, pp. 243–246 (2015)

    Google Scholar 

  45. Song, I.Y., Allen, R.B., Obradovic, Z., Song, M.: Keyphrase extraction-based query expansion in digital libraries. In: JCDL, pp. 202–209 (2006)

    Google Scholar 

  46. Tan, C., Card, D., Smith, N.A.: Friendships, rivalries, and trysts: Characterizing relations between ideas in texts. arXiv preprint arXiv:1704.07828 (2017)

  47. Teregowda, P., Urgaonkar, B., Giles, C.L.: Cloud 2010. In: 2010 IEEE 3rd International Conference on Cloud Computing, pp. 115–122 (2010)

    Google Scholar 

  48. Treeratpituk, P., Giles, C.L.: Disambiguating authors in academic publications using random forests. In: JCDL, pp. 39–48. ACM (2009)

    Google Scholar 

  49. Wan, X., Xiao, J.: Single document keyphrase extraction using neighborhood knowledge. AAAI. 8, 855–860 (2008)

    Google Scholar 

  50. Williams, K., Wu, J., Choudhury, S.R., Khabsa, M., Giles, C.L.: Scholarly big data information extraction and integration in the citeseer digital library. IIWeb, pp. 68–73 (2014)

    Google Scholar 

  51. Wu, J., Kandimalla, B., Rohatgi, S., Sefid, A., Mao, J., Giles, C.L.: Citeseerx-2018: a cleansed multidisciplinary scholarly big dataset. In: IEEE Big Data, pp. 5465–5467 (2018)

    Google Scholar 

  52. Wu, J., et al.: Pdfmef: a multi-entity knowledge extraction framework for scholarly documents and semantic search. In: K-CAP, pp. 13:1–13:8. ACM (2015)

    Google Scholar 

  53. Wu, J., Liang, C., Yang, H., Giles, C.L.: Citeseerx data: Semanticizing scholarly papers. In: SBD, pp. 2:1–2:6. ACM (2016)

    Google Scholar 

  54. Wu, J., et al.: CiteSeerX: AI in a digital library search engine. In: AAAI, pp. 2930–2937 (2014)

    Google Scholar 

  55. Zhang, Y., Milios, E., Zincir-Heywood, N.: A comparative study on key phrase extraction methods in automatic web site summarization. JDIM 5(5), 323 (2007)

    Google Scholar 

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Acknowledgements

We thank the National Science Foundation (NSF) for support from grants CNS-1853919, IIS-1914575, and IIS-1813571, which supported this research. Any opinions, findings, and conclusions expressed here are those of the authors and do not necessarily reflect the views of NSF. We also thank our anonymous reviewers for their constructive feedback.

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Authors and Affiliations

  1. Computer Science, Kansas State University, Manhattan, USA

    Krutarth Patel

  2. Computer Science, University of Illinois at Chicago, Chicago, USA

    Cornelia Caragea

  3. Computer Science, Old Dominion University, Norfolk, USA

    Jian Wu

  4. Information Sciences and Technology, Pennsylvania State University, State College, USA

    C. Lee Giles

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  1. Krutarth Patel
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  2. Cornelia Caragea
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  3. Jian Wu
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Corresponding authors

Correspondence to Krutarth Patel , Cornelia Caragea , Jian Wu or C. Lee Giles .

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Editors and Affiliations

  1. Auburn University, Auburn, AL, USA

    Wei-Shinn Ku

  2. Fujitsu (Japan), Kanagawa, Japan

    Yasuhiko Kanemasa

  3. United Arab Emirates University, Al Ain, United Arab Emirates

    Mohamed Adel Serhani

  4. Kingdee International Software Group Co., Ltd., Shenzhen, China

    Liang-Jie Zhang

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Patel, K., Caragea, C., Wu, J., Giles, C.L. (2020). Keyphrase Extraction in Scholarly Digital Library Search Engines. In: Ku, WS., Kanemasa, Y., Serhani, M.A., Zhang, LJ. (eds) Web Services – ICWS 2020. ICWS 2020. Lecture Notes in Computer Science(), vol 12406. Springer, Cham. https://doi.org/10.1007/978-3-030-59618-7_12

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  • DOI: https://doi.org/10.1007/978-3-030-59618-7_12

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