Abstract
The biomedical literature is growing at a double-exponential pace. Passage-level retrieval is more effective to provide the information section than document-level retrieval. This paper presents a method of two phase indexes based passage retrieval. First two phase indexes: paragraph index and sentence-level half-overlapped windows index are built. Then, BM25 model is used to retrieval on the two phase indexes. At last, the passage and paragraph retrieval results are combined as the result of the passage retrieval. The experiment result shows that the performance is improved 5% with two phase indexes than only with the paragraph index.
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References
Hersh, W., Cohen, A.M., Roberts, P., Rekapalli, H.K.: TREC 2006 Genomics Track Overview. In: Proceedings of the 15th Text REtrieval Conference (2006)
Jiang, J., Zhai, C.: Extraction of coherent relevant passages using hidden Markov models. ACM Transactions on Information Systems 24(3), 295–319 (2006)
Ofoghi, B., Yearwood, J., Jan, R.G.: A semantic approach to boost passage retrieval effectiveness for question answering. In: Proceedings of the 29th Australasian Computer Science Conference, pp. 95–101 (2006)
Hearst, M.: TextTiling: Segmenting Text into Multi-Paragraph Subtopic Passages. Computational Linguistics 23(1), 33–64 (1997)
Callan, J.P.: Passage-level evidence in document retrieval. In: SIGIR. Proceedings of the 17th annual international ACM-SIGIR conference on research and developments in information retrieval, Dublin, Ireland, New York, pp. 302–310. ACM Press, New York (1994)
Liu, X., Croft, W.B.: Passage: Retrieval Based on Language Models. In: Proceedings of the 11th International Conference on Information and Knowledge Management, pp. 375–382 (2002)
Kaszkiel, M., Zobel, J.: Effective ranking with arbitrary passages. Journal of the American Society For Information Science and Technology 52(4), 344–364 (2001)
Ponte, J.M., Bruce Croft, W.: A language modeling approach to information retrieval. In: SIGIR. Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Melbourne, Australia, pp. 275–281. ACM Press, New York (1998)
Jiang, J., Zhai, C.: UIUC in HARD 2004–Passage retrieval using HMMs. In: Proceedings of the 13th Text REtrieval Conference2004 (2004)
Huang, X., Huang, Y., Wen, M., et al.: York University at TREC 2004: HARD and Genomics Tracks. In: Proceedings of the 13th Text REtrieval Conference (2004)
Lin, K.H.-Y., Hou, W.-J., Chen, H.-H.: Retrieval of Biomedical Documents by Prioritizing Key Phrases. In: Proceedings of the 14th Text REtrieval Conference, Gaithersburg, Maryland (2005)
Zhai, C., Lu, X., Ling, X., He, X., Velivelli, A., Wang, X., Fang, H., Shakery, A.: UIUC/MUSC at TREC 2005 Genomics Track. In: Proceedings of the 14th Text REtrieval Conference (2006)
Strohman, T., Metzler, D., Turtle, H., Croft, W.B.: Indri: A language model based search engine for complex queries. In: Proceedings of the International Conference on Intelligence Analysis (2004)
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© 2007 Springer-Verlag Berlin Heidelberg
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Chen, R., Lin, H., Yang, Z. (2007). Two Phase Indexes Based Passage Retrieval in Biomedical Texts. In: Li, K., Fei, M., Irwin, G.W., Ma, S. (eds) Bio-Inspired Computational Intelligence and Applications. LSMS 2007. Lecture Notes in Computer Science, vol 4688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74769-7_79
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DOI: https://doi.org/10.1007/978-3-540-74769-7_79
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74768-0
Online ISBN: 978-3-540-74769-7
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