Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/397690
Title: Entity based query processing for retrieval and summarization in biomedical domain
Researcher: Sankhavara, Jainisha
Guide(s): Majumder, Prasenjit
Keywords: Engineering and Technology
Engineering
Engineering Biomedical
Database searching
Information retrieval
Semantic networks (Information theory)
University: Dhirubhai Ambani Institute of Information and Communication Technology (DA-IICT)
Completed Date: 2021
Abstract: quotExponential growth of biomedical literature poses different challenges in searching. To address complex information needs of the users, rigorous semantic processing of biomedical text is required. Biomedical information access emerges out as a new discipline for this reason. Traditional information access methods of matching, ranking, entity processing, entity-entity relationship processing, etc. are challenged in this domain. These are the major building blocks used to frame queries that represent complex information need in the area of biomedical and clinical information access. This thesis aims to do query processing using different IR and bioNLP techniques and to study their effects in retrieval and summarization. Various techniques of biomedical query reformulations are carried out and compared for biomedical document retrieval. Query expansion is one query reformulation technique which was carried out using relevance feedback and pseudo relevance feedback for biomedical document retrieval. Relevance feedback approach uses information regarding actual relevant documents to the query for feedback while pseudo relevance feedback approach does not have such information and uses top retrieved documents for feedback as they are assumed to be relevant to the query. One combined approach of relevance feedback and pseudo relevance feedback has been proposed which is based on feedback document discovery and uses various classification and clustering techniques on biomedical documents newlineto identify good document for feedback. This approach uses relevance feedback for a number of documents and tries to learn relevance for other documents for feedback. This feedback document discovery based query expansion approach shows improvement over relevance feedback based query expansion technique for biomedical document retrieval. newlineAn improved version of this feedback document discovery based query expansion approach where the features of entities are weighted based on the type of the entities and query is also proposed which...
Pagination: xi, 115 p.
URI: http://hdl.handle.net/10603/397690
Appears in Departments:Department of Information and Communication Technology

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02_decalaration and certificate.pdf96.98 kBAdobe PDFView/Open
03_acknowledgments.pdf47.73 kBAdobe PDFView/Open
04_contents.pdf53.48 kBAdobe PDFView/Open
05_abstract.pdf50.33 kBAdobe PDFView/Open
06_list of tables and list of figures.pdf70.7 kBAdobe PDFView/Open
07_chapter 1.pdf221.25 kBAdobe PDFView/Open
08_chapter 2.pdf316.71 kBAdobe PDFView/Open
09_chapter 3.pdf847.63 kBAdobe PDFView/Open
10_chapter 4.pdf1.36 MBAdobe PDFView/Open
11_chapter 5.pdf205.92 kBAdobe PDFView/Open
12_chapter 6.pdf49.64 kBAdobe PDFView/Open
13_references.pdf114.16 kBAdobe PDFView/Open
14_list of publications.pdf62.88 kBAdobe PDFView/Open
80_recommendation.pdf83.07 kBAdobe PDFView/Open
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