Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/303691
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dc.coverage.spatialEnhanced automatic extraction of target-based multi-word expression with clustering technique for opinion mining
dc.date.accessioned2020-10-21T10:59:40Z-
dc.date.available2020-10-21T10:59:40Z-
dc.identifier.urihttp://hdl.handle.net/10603/303691-
dc.description.abstractInformation Extraction IE is an automatic extraction of required text from semistructured or unstructured environments This text data is categorized into objective and subjective sentences An objective sentence contains factual that is true information about the world and subjective sentence contains some personal opinions or views Retrieving information from subjective sentence is an emerging research trend Opinion Mining is the study of users opinion about a product and/or service from plain text which is either done at the sentence document or target level This research concentrates on target level also known as aspect or feature Opinion Mining from different customer reviews Here target level extracts the detailed information about the targets or features of the product and services It deals with the opinions of entities andor targets and their corresponding polarities such as positive negative or neutral Usually two types of targets are present in the customer reviews namely Explicit directly mentioning the targets and Implicit indirectly mentioning the targets Finetuned opinion extraction is performed based on these targets in which the customers opinion has been expressed In recent research of Opinion Mining researchers have applied innovative techniques like target extraction topic modelling in domain independent customer reviews and in Microblogging posts at Facebook and Twitter However these techniques are generally sensitive to extract exact targets and their opinions since they extract the result data in an insignificant way newline
dc.format.extentxxiv,174p.
dc.languageEnglish
dc.relationp.161-173.
dc.rightsuniversity
dc.titleEnhanced automatic extraction of target based multi word expression with clustering technique for opinion mining
dc.title.alternative
dc.creator.researcherPradeepa M
dc.subject.keywordEngineering and Technology
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordInformation Extraction
dc.subject.keywordOpinion Mining
dc.subject.keywordRetrieving information
dc.description.note
dc.contributor.guideDeisy C
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registeredn.d.
dc.date.completed2019
dc.date.awarded2019
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File24.68 kBAdobe PDFView/Open
02_certificates.pdf492.65 kBAdobe PDFView/Open
03_abstracts.pdf67.54 kBAdobe PDFView/Open
04_acknowledgements.pdf6.2 kBAdobe PDFView/Open
05_contents.pdf13.86 kBAdobe PDFView/Open
06_list_of_tables.pdf7.03 kBAdobe PDFView/Open
07_list_of_figures.pdf61.53 kBAdobe PDFView/Open
08_list_of_abbreviations.pdf172.55 kBAdobe PDFView/Open
09_chapter1.pdf404.38 kBAdobe PDFView/Open
10_chapter2.pdf562.53 kBAdobe PDFView/Open
11_chapter3.pdf1.23 MBAdobe PDFView/Open
12_chapter4.pdf1.56 MBAdobe PDFView/Open
13_chapter5.pdf625.96 kBAdobe PDFView/Open
14_chapter6.pdf938.89 kBAdobe PDFView/Open
15_conclusion.pdf105.79 kBAdobe PDFView/Open
16_appendices.pdf245.43 kBAdobe PDFView/Open
17_references.pdf184.98 kBAdobe PDFView/Open
18_list_of_publications.pdf109.77 kBAdobe PDFView/Open
80_recommendation.pdf193.41 kBAdobe PDFView/Open


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