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Warianty tytułu
Konferencja
Federated Conference on Computer Science and Information Systems (15 ; 06-09.09.2020 ; Sofia, Bulgaria)
Języki publikacji
Abstrakty
Information Retrieval is about user queries and strategies executed by machines to find the documents that best suit the user's information need. However, this need reduced to a couple of words gives the retrieval system (IRS) a lot room for interpretation. In order to zero in on the user's need many a IRS expands the user query by implicitly adding or explicitly recommending the users further useful terms that help to specify their information need. Queries often do not comprise more than a handful of terms, which, in turn, do not sufficiently represent the user's need. In this paper, we propose and demonstrate an approach that enables users to resort to implicitly more complex query expressions. We call these semantic structures concept blueprints. Furthermore, users have the possibility to define the blueprints on their own. The purpose of the blueprints is to spot more precisely the text passage that fits the user's information need.
Rocznik
Tom
Strony
45--48
Opis fizyczny
Bibliogr. 13 poz., rys.
Twórcy
autor
- Schmalkalden University of Applied Science, Blechhammer, 98574 Schmalkalden, Germany
Bibliografia
- 1. J. L. Kolodner, “Requirements for natural language fact retrieval”, Proceedings of the ACM '82 conference, 1982, pp. 192–198.
- 3. N. Fuhr, “Integration of probabilistic fact and text retrieval”, Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval, 1992, pp 211–222.
- 4. M. Keikha, J. H. Park, W. B. Croft, and M. Sanderson, “Retrieving Passages and Finding Answers”, Proceedings of the 2014 Australasian Document Computing Symposium, 2014, 81–84.
- 5. N. Balasubramanian, J. Allan, and W. B. Croft, “A comparison of sentence retrieval techniques”, Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, 2007, pp. 813–814.
- 6. R. W. White, S. M. Drucker, G. Marchionini, M. Hearst, and M. C. Schraefel, “Exploratory search and HCI: designing and evaluating interfaces to support exploratory search interaction”, CHI '07 Extended Abstracts on Human Factors in Computing Systems, 2007, pp. 2877–2880.
- 7. A. T. Nguyen, A. Kharosekar, S. Krishnan, and S. Krishnan, “Believe it or not: Designing a Human-AI Partnership for Mixed-Initiative Fact-Checking”, Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology, 2018, pp. 189–199.
- 8. H. E. Wynne and Z. Z. Wint, “Content Based Fake News Detection Using N-Gram Models”. Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services (iiWAS2019), 2019, pp. 669–673.
- 9. W. A. Woods, “Context-Sensitive Parsing”. Communications of the ACM 13(7), 1996, pp. 413–445.
- 10. F. Sha, F. and F. Pereira, F., “Shallow Parsing with Conditional Random Fields”, Proceedings of the HLT-NAACL conference, 2003, pp. 134-141.
- 11. D. Freitag and A. McCallum, “Information Extraction with HMM Structures Learned by Stochastic Optimization”, Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence, 2000, pp. 584-589.
- 12. J. Cowie and W. Lehnert, “Information Extraction”. Communications of the ACM 39(1): 80–91.
- 13. G. Salton, J. Allan, C. Buckely, A. Singhal, “Automatic Analysis, Theme Generation, and Summarization of Machine-Readable Texts”, in: Karen Sparck Jones and Peter Willett, Readings in Information Retrieval, San Francisco, 1997, pp. 478–483.
- 14. J. Jancsary, F. Neubarth, S. Schreitter, and H. Trost, “Towards a context-sensitive online newspaper”. Proceedings of the 2011 Workshop on Context-awareness in Retrieval and Recommendation, 2011, pp. 2–9.
Uwagi
1. Track 1: Artificial Intelligence
2. Technical Session: 15th International Symposium Advances in Artificial Intelligence and Applications
3. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-83aaf4db-7539-4322-a789-fde7ed6b8ce7