Extraction of Relying Factors to be Diabetic in Pregnant Women using Attribute Mutual Information

  • et al.
Citations of this article
Mendeley users who have this article in their library.
Get full text


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.




Pavani*, N., Sujatha, Dr. V., & Chaitanya, P. S. (2019). Extraction of Relying Factors to be Diabetic in Pregnant Women using Attribute Mutual Information. International Journal of Innovative Technology and Exploring Engineering, 9(2), 4959–4961. https://doi.org/10.35940/ijitee.b9075.129219

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free