Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/431019
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dc.coverage.spatialCertain investigation on document Sentiment analysis and analyzing Discussions on online forum posts Using intelligent data mining Techniques
dc.date.accessioned2022-12-24T08:33:58Z-
dc.date.available2022-12-24T08:33:58Z-
dc.identifier.urihttp://hdl.handle.net/10603/431019-
dc.description.abstractSentiment Analysis or Opinion Mining is a Natural Language Processing method used to assess whether data is positive, negative or neutral. Sentiment Analysis is also conducted on textual information to help companies track brand and product sentiment in consumer reviews, and recognize customer demands. In recent days, Web search engine tools have been supporting people in the journey of information. From the record and ordering frameworks to the cutting edge million-results-under-a-second nature of inquiry frameworks are truly long voyages. A large portion of the web indexes accepts crude watchwords as a trigger to create the information from the huge stores for the most part. Several users provide reviews but only a few parameters are proven to be significant. The recommendation or opinion given to the potential user is based on the type of feedback. newlineFor the purpose of the experiment, many reviews were gathered and sentiment analysis was performed. The opinion polarity has been calculated using the automatic weighted method. The suggested solution outperforms the current methodology by applying the automatic weight. Using the proposed Multinomial Naive Bayes SVM (MNBSVM) classifier method the user reviews of mobile phones has been predicted with the help of positive and negative count reviews. The previous techniques focus on the sentiment scores generated by the class of documents upon collection, and it is a time consuming process. In order to overcome these problems, the proposed mechanism of Collective Parallel Cluster Algorithm has been developed. The proposed model performs well in terms of accuracy, lesser human intervention with efficiency and feasibility analysis. newline
dc.format.extentxvi,125p.
dc.languageEnglish
dc.relationp.118-124
dc.rightsuniversity
dc.titleCertain investigation on document Sentiment analysis and analyzing Discussions on online forum posts Using intelligent data mining Techniques
dc.title.alternative
dc.creator.researcherRasikannan, L
dc.subject.keywordEngineering and Technology
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keyworddata mining
dc.subject.keywordSentiment analysis
dc.description.note
dc.contributor.guideAlli, P
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2021
dc.date.awarded2021
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 File41.8 kBAdobe PDFView/Open
02_prelim pages.pdf3.13 MBAdobe PDFView/Open
03_content.pdf108.05 kBAdobe PDFView/Open
04_abstract.pdf52.14 kBAdobe PDFView/Open
05_chapter 1.pdf860.46 kBAdobe PDFView/Open
06_chapter 2.pdf603.58 kBAdobe PDFView/Open
07_chapter 3.pdf343.44 kBAdobe PDFView/Open
08_chapter 4.pdf962.79 kBAdobe PDFView/Open
09_chapter 5.pdf966.96 kBAdobe PDFView/Open
10_chapter 6.pdf903.74 kBAdobe PDFView/Open
11_chapter 7.pdf221.22 kBAdobe PDFView/Open
12_annexures.pdf109.28 kBAdobe PDFView/Open
80_recommendation.pdf115.55 kBAdobe PDFView/Open


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