The objective of this monograph is to improve the performance of the sentiment analysis model by incorporating the semantic, syntactic and common-sense knowledge. This book proposes a novel semantic concept extraction approach that uses dependency relations between words to extract the features from the text. Proposed approach combines the semantic and common-sense knowledge for the better understanding of the text. In addition, the book aims to extract prominent features from the unstructured text by eliminating the noisy, irrelevant and redundant features. Readers will also discover a proposed method for efficient dimensionality reduction to alleviate the data sparseness problem being faced by machine learning model. Authors pay attention to the four main findings of the book : -Performance of the sentiment analysis can be improved by reducing the redundancy among the features. Experimental results show that minimum Redundancy Maximum Relevance (mRMR) feature selection technique improves the performance of the sentiment analysis by eliminating the redundant features. - Boolean Multinomial Naive Bayes (BMNB) machine learning algorithm with mRMR feature selection technique performs better than Support Vector Machine (SVM) classifier for sentiment analysis. - The problem of data sparseness is alleviated by semantic clustering of features, which in turn improves the performance of the sentiment analysis. - Semantic relations among the words in the text have useful cues for sentiment analysis. Common-sense knowledge in form of ConceptNet ontology acquires knowledge, which provides a better understanding of the text that improves the performance of the sentiment analysis.
India is shining, and Suresh Kaushal, the stout lawyer -of sober habits', has propelled himself up the political ladder to become Minister of State for Food Processing, Animal Husbandry, Fisheries and Canneries. His wife Priya can't believe their luck and, determined to ensure it doesn't run out, struggles valiantly with -social vertigo', infidelity and menopause. Along the way she also learns vital lessons on survival, as she watches her glamorous new friend Pooonam chase status, sex and Jimmy Choo shoes, and her radical old friend Lenin ride a donkey and lose his bearings. In this wickedly funny, occasionally tender, book, Namita Gokhale resurrects some unforgettable characters from her 1984 cult bestseller Paro, and plunges them neck-deep into Delhi's toxic waste of power, money and greed.
Legal issues in medical practice have been gripping medical doctors by surprise in recent years. Some decades ago legal issues in medical practice never created any problem. A greater awareness is being created by adding doctor’s services within the ambit of Consumer Protection Act, 1986. Neither during the undergraduate training nor the postgraduate courses doctors have ever prepared themselves to deal with real-world situations of litigation related to allegations of negligence. While facing litigation related to allegation of negligence in law courts for the first time, a doctor realizes the importance of medical records, consent and expert witness and searches for help books. There are many books available for reference but this one is a handbook for practising doctors and their lawyers grappled with legal issues culminating in litigations covering a vast number of medical specialties and systems.This book proposes to fill the existing vacuum by creating authentic base required to understand the legal issues in medical practice in India. The esteemed contributors have put in their best efforts to share their knowledge, experience and wisdom with the readers by discussing various landmark legal decisions in the field of (alleged) medical negligence. It aims to make the medical practice safe, ethical, reassuring and hassle-free by discussing various legal issues related to medical practice.
The starting point for the book is the low economic activity of women in India, and hence, both governmental and NGO-based activities to raise the level of women’s participation to Indian economy, and through that, the increase in women’s economic and social independence. The book focuses on elementary and important issues of entrepreneurship and women in any economy. Prof. Anne Kovalainen School of Economics University of Turku, Finland The book focuses on three NGOs and their activities in enhancing and promoting women’s entrepreneurial activities in three different areas in India. The empirical material consists of interview materials as well as background data and reports, national level statistics and other figures that are used to describe the Indian situation in general, and specifically those conditions from where women’s entrepreneurial activities arise, such as gender equality and legislation frameworks. The book is very important, not only for the women’s entrepreneurship and economic activity but for the Indian society at large. Prof. Paola Villa Department of Economics University of Trento, Italy This book is a product of extensive and intensive research. The book aptly highlights and proves the importance of NGOs in promoting women entrepreneurship. Given the rigors of research methodology, the book will also serve as a model for future research on the related dimensions of women entrepreneurship. Prof. Italo Trevisan Department of Economics and Management University of Trento, Italy Women’s empowerment in India remains a daunting task for governmental and non-governmental organizations alike. Given the importance of economic empowerment of women, this study provides an overview of the entrepreneurship as a means to economic empowerment of Indian women. Dr. Suman Sharma Officer on Special Duty(OSD) Dayal Singh College (Evening) University of Delhi
Introduction : An asynchronic timeline -- Ephemeral infrastructures -- The financial sublime -- Drawing fantasies -- The industry of sound -- Inside the pit -- Concrete love -- Conclusion : Inquilab zindabad -- Appendix : list of masterplans affecting gurgaon.
This book provides useful information on microbial physiology and metabolism. The key aspects covered are prokaryotic diversity, growth physiology, basic metabolic pathways and their regulation, metabolic diversity with details of various unique pathways. Another focus area is stress physiology with details on varying environmental stresses, signal transduction, adaptation and survival. For instructional purposes, the book provides case studies, interesting facts, techniques etc. which help in showcasing the inter-disciplinary nature and bridge the gap between various aspects of applied microbiology.
The objective of this monograph is to improve the performance of the sentiment analysis model by incorporating the semantic, syntactic and common-sense knowledge. This book proposes a novel semantic concept extraction approach that uses dependency relations between words to extract the features from the text. Proposed approach combines the semantic and common-sense knowledge for the better understanding of the text. In addition, the book aims to extract prominent features from the unstructured text by eliminating the noisy, irrelevant and redundant features. Readers will also discover a proposed method for efficient dimensionality reduction to alleviate the data sparseness problem being faced by machine learning model. Authors pay attention to the four main findings of the book : -Performance of the sentiment analysis can be improved by reducing the redundancy among the features. Experimental results show that minimum Redundancy Maximum Relevance (mRMR) feature selection technique improves the performance of the sentiment analysis by eliminating the redundant features. - Boolean Multinomial Naive Bayes (BMNB) machine learning algorithm with mRMR feature selection technique performs better than Support Vector Machine (SVM) classifier for sentiment analysis. - The problem of data sparseness is alleviated by semantic clustering of features, which in turn improves the performance of the sentiment analysis. - Semantic relations among the words in the text have useful cues for sentiment analysis. Common-sense knowledge in form of ConceptNet ontology acquires knowledge, which provides a better understanding of the text that improves the performance of the sentiment analysis.
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