Extraction of Relying Factors to be Diabetic in Pregnant Women using Attribute Mutual Information
N.Pavani1, V.Sujatha2, P.Silpa Chaitanya3
1Pavani*, Asst. Professor, Department of Computer Science and Engineering, Vignan‟s Nirula Institute of Technology Science and Women, AP, India
2Dr.V.Sujatha, Professor, Department of Computer Science and Engineering, Vignan‟s Nirula Institute of Technology Science and Women, AP, India.
3P.Silpa Chaitanya, Asst.professor, Department of Computer Science and Engineering, Vignan‟s Nirula Institute of Technology Science and Women, AP, India.
Manuscript received on November 15, 2019. | Revised Manuscript received on 26 November, 2019. | Manuscript published on December 10, 2019. | PP: 4959-4961 | Volume-9 Issue-2, December 2019. | Retrieval Number: B9075129219/2019©BEIESP | DOI: 10.35940/ijitee.B9075.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Since a decade research over sentiment analysis and opinion mining was evolving slowing and emerging widely with greater perspectives and objectives. Sentiment analysis is an important task in order to gain insights over the huge amounts of opinions that are generated on a daily basis. This analysis relies on the opinions made by the individuals. These opinions are text, may be positive or negative or a phrase which gives significance to the context. Also these opinions have the power of expressing the context besides drags the attention of new folks. Expressing such opinions ranges from documents level, to the sentence level, to phrase level, to word level and to special symbol level. All these opinion types are labelled with common name Sentiment Analysis. Sentiment Analysis is health care is evolving narrowly with wider research strings. This paper mainly focuses in identifying Sentiments in health care. These sentiments can be medical test values which may be numeric and nominal; sometimes in text too. Such sentiments are identified with pre-fragmentation of data set and Pointwise Mutual Information measure. To accomplish this data of hypertensive pregnant women is considered.
Keywords: Horizontal Fragmentation, Pointwise Mutual Information, Sentiment Analysis.
Scope of the Article: Healthcare Informatics