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  Authors

Malla Rukmini Durga ,V. V. Sivarama ,M Srihari Varma

  Keywords

A Machine Learning Approach for Identifying Disease-Treatment Relations in Short Texts

  Abstract


Medical information retrieval plays an increasingly important role to help physicians and domain experts to better access medical related knowledge and information, and support decision making. Integrating the medical knowledge bases has the potential to improve the information retrieval performance through incorporating medical domain knowledge for relevance assessment. However, this is not a trivial task because of the challenges to effectively utilize the domain knowledge in the medical knowledge bases. In this paper, we proposed a novel medical information retrieval system with a two-stage query expansion strategy, which is able to effectively model and incorporate the latent semantic associations to improve the performance. This system consists of two parts. First, we applied a heuristic approach to enhance the widely used pseudo relevance feedback method for more effective query expansion, through iteratively expanding the queries to boost the similarity score between queries and documents. Second, to improve the retrieval performance with structured knowledge bases, we presented a latent semantic relevance model based on tensor factorization to identify semantic association patterns under sparse settings. These identified patterns are then used as inference paths to trigger knowledge-based query expansion in medical information retrieval. Experimentsshowed that the performance of the proposed system is significantly better than the baseline system, and is comparable with state-of-the-art systems; (b) demonstrated the capability of tensor-based semantic enrichment methods for medical information retrieval tasks.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT1704370

  Paper ID - 170944

  Author type - Indian Author

  Page Number(s) - 2804-2809

  Pubished in - Volume 5 | Issue 4 | December 2017

  DOI (Digital Object Identifier) -   

  No Of Downloads - 1129

  Author Country - -, -, -, -, -, Science & Technology

  Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Published Paper PDF : - http://www.ijcrt.org/papers/IJCRT1704370

  Published Paper URL: : - http://ijcrt.org/viewfull.php?&p_id=IJCRT1704370

  Published Paper PDF Downlaod: - download.php?file=IJCRT1704370

  Cite this article

Malla Rukmini Durga ,V. V. Sivarama ,M Srihari Varma ,   "A MACHINE LEARNING APPROACH FOR IDENTIFYING DISEASE-TREATMENT RELATIONS IN SHORT TEXTS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.5, Issue 4, pp.2804-2809, December 2017, Available at :http://www.ijcrt.org/papers/IJCRT1704370.pdf

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