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The web propounds a wealth of information on reviews that can invigorate decision making tasks ranging from which product to purchase to which doctor to consult for a particular ailment. Due to the colossal volume of reviews available from different sources across web, managing all the available opinions is a protracted process which can rigorously impair user productivity. As a result, these valuable reviews provide colossal data of opinions that impedes instead of helping in decision making scenarios especially those involving a large number of entities.In this book, we postulate an adroit…mehr

Produktbeschreibung
The web propounds a wealth of information on reviews that can invigorate decision making tasks ranging from which product to purchase to which doctor to consult for a particular ailment. Due to the colossal volume of reviews available from different sources across web, managing all the available opinions is a protracted process which can rigorously impair user productivity. As a result, these valuable reviews provide colossal data of opinions that impedes instead of helping in decision making scenarios especially those involving a large number of entities.In this book, we postulate an adroit way of summarizing the reviews, that is to adhere the strengths of search technologies with opinion analysis and mining tools to provide a powerful decision making platform. This book illustrates techniques from Machine Learning that can be leveraged for Feature Extraction and Summarizing Health Reviews.
Autorenporträt
Mozibur Raheman Khan works for Jamal Mohamed College (Auto), Tiruchirappalli, India as an Assistant Professor of Computer Applications. Rajkumar Kannan is the Speaker, Consultant and Dean at Bishop Heber College (Auto), Tiruchirappalli, India. He is a Data Science and AI Thought Leader and Senior Member of ACM-USA and Life Member of CSI and ISTE.