Entity based query processing for retrieval and summarization in biomedical domain

dc.contributor.guideMajumder, Prasenjit
dc.coverage.spatial
dc.creator.researcherSankhavara, Jainisha
dc.date.accessioned2022-08-05T05:59:48Z
dc.date.available2022-08-05T05:59:48Z
dc.date.awarded2021
dc.date.completed2021
dc.date.registered2015
dc.description.abstractquotExponential 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...
dc.description.note
dc.format.accompanyingmaterialNone
dc.format.dimensions30 cm
dc.format.extentxi, 115 p.
dc.identifier.urihttp://hdl.handle.net/10603/397690
dc.languageEnglish
dc.publisher.institutionDepartment of Information and Communication Technology
dc.publisher.placeGandhinagar
dc.publisher.universityDhirubhai Ambani Institute of Information and Communication Technology (DA-IICT)
dc.relationSankhavara, Jainisha, Entity based query processing for retrieval and summarization in biomedical domain; xi, 115 p.; 2021. (Supervisor: Prasenjit Majumder)
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering
dc.subject.keywordEngineering Biomedical
dc.subject.keywordDatabase searching
dc.subject.keywordInformation retrieval
dc.subject.keywordSemantic networks (Information theory)
dc.titleEntity based query processing for retrieval and summarization in biomedical domain
dc.title.alternative
dc.type.degreePh.D.

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