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Book ChapterDOI

Techniques, Applications, and Issues in Mining Large-Scale Text Databases

TLDR
The main objective is to review text mining techniques, application areas, and existing issues.
Abstract
The discovery of knowledge from large-scale text data or semi-structured data is very difficult. In text mining, useful information is extracted out of such large text corpus which fulfills a user current information need. This process is being exploited by various organizations for quality improvement, business need, and understanding user behavior. The text available in unstructured and semi-structured form can come through sources such as medical, financial, market, scientific, and others documents. Text mining applies quantitative approach to analyze massive amount of textual data and tries to solve information overload problem. The main objective is to review text mining techniques, application areas, and existing issues.

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Citations
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Book ChapterDOI

Processing Large Text Corpus Using N-Gram Language Modeling and Smoothing

TL;DR: In this article, N-gram models are discussed and evaluated using Good Turing Estimation, perplexity measure and type-to-token ratio to predict the next word when the user provides input.
Book ChapterDOI

Augmenting Mental Healthcare With Artificial Intelligence, Machine Learning, and Challenges in Telemedicine

TL;DR: The goal of this chapter is to review the literature on artificial intelligence and machine learning algorithms for detecting a person's mental health by utilizing patient health records and explains the use of artificial intelligence in curing and monitoring a patient with mental illness through telemedicine.
Journal ArticleDOI

Sentiment Analysis of Public Social Media as a Tool for Health-Related Topics

TL;DR: Specific applications related to the extraction and classification of social media data using novel SA techniques are presented and quantified, with an emphasis on those used for the identification of mental health degradation during the COVID-19 pandemic.
Journal ArticleDOI

Higher Employee Engagement through Social Intelligence: A Perspective of Indian Scenario

TL;DR: In this article , the authors found that high levels of social intelligence are required for effective engagement, and they set out to find the association between employee engagement and social intelligence by conducting a statistical analysis.
References
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Journal ArticleDOI

The Survey of Data Mining Applications And Feature Scope

TL;DR: In this paper, a variety of techniques, approaches and different areas of the research which are helpful and marked as the important field of data mining Technologies are focused.
Journal ArticleDOI

Data mining cluster analysis on the influence of health factors in Casemix data.

TL;DR: This study explores potential data mining applications in the Casemix context, which is expected to yield effective and efficient health care services by determining hidden relevant patterns which can’t be processed by human capabilities all alone.
Journal ArticleDOI

Determining the difficulty of Word Sense Disambiguation

TL;DR: Various methods for estimating the performance of WSD systems on a wide range of ambiguous biomedical terms (including ambiguous words/phrases and abbreviations) are explored, finding the supervised methods are the best predictors of W SD difficulty, but are limited by their dependence on labeled training data.
Journal ArticleDOI

Ensembles of randomized trees using diverse distributed representations of clinical events

TL;DR: The strategy for utilizing a set of diverse distributed representations of clinical events when constructing ensembles of randomized trees has a significant impact on predictive performance and that performance tends to improve as the size increases.