Skip to main content
SpringerLink
Log in

Event-Based Recognition of Lived Experiences in User Reviews

  • Conference paper
  • First Online:
Knowledge Engineering and Knowledge Management (EKAW 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10024))

Included in the following conference series:

  • 2187 Accesses

Abstract

User reviews on the web are an important source of opinions on products and services. For a popular product or service, the number of reviews can be large. Therefore, it may be difficult for a potential customer to read all of them and make a decision. We hypothesize and test if lived experiences from reviews may support the confidence of a user in a review. We identify and extract such lived experiences with a novel technique based on machine reading. Our experimental results demonstrate the effectiveness of the technique.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://lipn.univ-paris13.fr/ClientProj/client.jsp.

  2. 2.

    http://wit.istc.cnr.it/stlab-tools/fred.

  3. 3.

    Available by request at: http://www.cs.cornell.edu/~myleott/op_spam.

  4. 4.

    http://www.tripadvisor.com/.

  5. 5.

    https://github.com/asgordon/StoryNonstory.

  6. 6.

    https://lipn.univ-paris13.fr/ClientProj/client.jsp.

References

  1. Aone, C., Ramos-Santacruz, M.: REES: a large-scale relation and event extraction system. In: Proceedings of the Sixth Conference on Applied Natural Language Processing, pp. 76–83 (2000)

    Google Scholar 

  2. Barsalou, L.W.: The content and organization of autobiographical memories. In: Remembering Reconsidered: Ecological and Traditional Approaches to the Study of Memory, pp. 193–243 (1988)

    Google Scholar 

  3. Baumgartner, H., Sujan, M., Bettman, J.R.: Autobiographical memories, affect, and consumer information processing. J. Consum. Psychol. 1, 53–82 (1992)

    Article  Google Scholar 

  4. Bethard, S., Martin, J.H.: Identification of event mentions and their semantic class. In: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, pp. 146–154 (2006)

    Google Scholar 

  5. Duffy, A.M.: Fellow travellers: what do users trust on recommender websites? A case study of TripAdvisor.com. Ph.D. thesis (2012)

  6. Eastmond, M.: Stories as lived experience: narratives in forced migration research. J. Refugee Stud. 20, 248–264 (2007)

    Article  Google Scholar 

  7. Etzioni, O., Banko, M., Cafarella, M.: Machine reading. In: Proceedings of the 21st National Conference on Artificial Intelligence (AAAI) (2006)

    Google Scholar 

  8. Gangemi, A.: A comparison of knowledge extraction tools for the semantic web. In: Cimiano, P., Corcho, O., Presutti, V., Hollink, L., Rudolph, S. (eds.) ESWC 2013. LNCS, vol. 7882, pp. 351–366. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  9. Gangemi, A., Hassan, E., Presutti, V., Reforgiato, D.: Fred as an event extraction tool. In: Proceedings of the Workshop on Detection, Representation, and Exploitation of Events in the Semantic Web, p. 14 (2013)

    Google Scholar 

  10. Gangemi, A., Presutti, V., Recupero, D.R., Nuzzolese, A.G., Draicchio, F., Mongiovi, M.: Semantic web machine reading with FRED. In: Sermantic Web (2016). http://www.semantic-web-journal.net/system/files/swj1297.pdf

  11. Gordon, A., Swanson, R.: Identifying personal stories in millions of weblog entries. In: Third International Conference on Weblogs and Social Media, Data Challenge Workshop, San Jose, CA (2009)

    Google Scholar 

  12. Gordon, A.S.: Story management technologies for organizational learning. In: International Conference on Knowledge Management. In Special Track on Intelligent Assistance for Self-directed and Organizational Learning, Graz, Austria (2008)

    Google Scholar 

  13. Hassan, E., Buscaldi, D., Gangemi, A.: Correlating open rating systems and event extraction from text. In: Arik, S., Huang, T., Lai, W.K., Liu, Q. (eds.) ICONIP 2015. LNCS, vol. 9492, pp. 367–375. Springer, Heidelberg (2015). doi:10.1007/978-3-319-26561-2_44

    Chapter  Google Scholar 

  14. Inui, K., Abe, S., Hara, K., Morita, H., Sao, C., Eguchi, M., Sumida, A., Murakami, K., Matsuyoshi, S.: Experience mining: building a large-scale database of personal experiences and opinions from web documents. In: Proceedings of the 2008 International Conference on Web Intelligence and Intelligent Agent Technology. IEEE Computer Society, Washington, DC (2008)

    Google Scholar 

  15. Jindal, N., Liu, B.: Opinion spam and analysis. In: Proceedings of the 2008 International Conference on Web Search and Data Mining, pp. 219–230. ACM (2008)

    Google Scholar 

  16. Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics 33, 159–174 (1977)

    Article  MathSciNet  MATH  Google Scholar 

  17. Ott, M., Choi, Y., Cardie, C., Hancock, J.T.: Finding deceptive opinion spam by any stretch of the imagination. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies-Vol. 1, pp. 309–319 (2011)

    Google Scholar 

  18. Pazzani, M.J., Billsus, D.: Content-based recommendation systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web. LNCS, vol. 4321, pp. 325–341. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  19. Ploeger, T., Kruijt, M., Aroyo, L., de Bakker, F., Hellsten, I., Fokkens, A., Hoeksema, J., ter Braake, S.: Extracting activist events from news articles using existing NLP tools and services. In: Proceedings of the Workshop on Detection, Representation, and Exploitation of Events in the Semantic Web, p. 30 (2013)

    Google Scholar 

  20. Presutti, V., Draicchio, F., Gangemi, A.: Knowledge Extraction based on discourse representation theory and linguistic frames. In: ten Teije, A., Völker, J., Handschuh, S., Stuckenschmidt, H., d’Acquin, M., Nikolov, A., Aussenac-Gilles, N., Hernandez, N. (eds.) EKAW 2012. LNCS, vol. 7603, pp. 114–129. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  21. Ritter, A., Etzioni, O., Clark, S., et al.: Open domain event extraction from twitter. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1104–1112 (2012)

    Google Scholar 

  22. Saurí, R., Knippen, R., Verhagen, M., Pustejovsky, J.: Evita: a robust event recognizer for QA systems. In: Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, pp. 700–707 (2005)

    Google Scholar 

  23. Treloar, C., Rhodes, T.: The lived experience of hepatitis c and its treatment among injecting drug users: qualitative synthesis. Qual. Health Res. 19, 1321–1334 (2009)

    Article  Google Scholar 

  24. Tung, V.W.S., Ritchie, J.B.: Exploring the essence of memorable tourism experiences. Ann. Tourism Res. 38, 1367–1386 (2011)

    Article  Google Scholar 

  25. Van Oorschot, G., Van Erp, M., Dijkshoorn, C.: Automatic extraction of soccer game events from twitter. In: Proceedings of the Workshop on Detection, Representation, and Exploitation of Events in the Semantic Web, p. 15 (2012)

    Google Scholar 

  26. Zhang, Y., Xu, C., Rui, Y., Wang, J., Lu, H.: Semantic event extraction from basketball games using multi-modal analysis. In: 2007 IEEE International Conference on Multimedia and Expo, pp. 2190–2193 (2007)

    Google Scholar 

Download references

Acknowledgements

I would like to thank Dr. Mehwish Alam for her suggestions. This work is partially supported by a public grant overseen by the French National Research Agency (ANR) as part of the program “Investissements d’Avenir” (reference: ANR-10-LABX-0083).

Author information

Authors and Affiliations

  1. LIPN, Université Paris XIII, CNRS UMR 7030, 93430, Villetaneuse, France

    Ehab Hassan, Davide Buscaldi & Aldo Gangemi

  2. STLab, ISTC-CNR, Rome, Italy

    Aldo Gangemi

Authors
  1. Ehab Hassan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Davide Buscaldi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Aldo Gangemi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ehab Hassan .

Editor information

Editors and Affiliations

  1. Linköping University, Linköping, Sweden

    Eva Blomqvist

  2. University of Bologna, Bologna, Italy

    Paolo Ciancarini

  3. University of Bologna, Bologna, Italy

    Francesco Poggi

  4. University of Bologna, Bologna, Italy

    Fabio Vitali

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing AG

About this paper

Cite this paper

Hassan, E., Buscaldi, D., Gangemi, A. (2016). Event-Based Recognition of Lived Experiences in User Reviews. In: Blomqvist, E., Ciancarini, P., Poggi, F., Vitali, F. (eds) Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science(), vol 10024. Springer, Cham. https://doi.org/10.1007/978-3-319-49004-5_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-49004-5_21

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49003-8

  • Online ISBN: 978-3-319-49004-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation