An Approach to Sentiment Analysis on Unstructured Data in Big Data Environment

Author(s):  
Dilipkumar A. Borikar ◽  
Manoj B. Chandak
2018 ◽  
Vol 33 (3) ◽  
pp. 187-202
Author(s):  
Wint Nyein Chan ◽  
Thandar Thein

Author(s):  
Emrah Inan ◽  
Burak Yonyul ◽  
Fatih Tekbacak

Most of the data on the web is non-structural, and it is required that the data should be transformed into a machine operable structure. Therefore, it is appropriate to convert the unstructured data into a structured form according to the requirements and to store those data in different data models by considering use cases. As requirements and their types increase, it fails using one approach to perform on all. Thus, it is not suitable to use a single storage technology to carry out all storage requirements. Managing stores with various type of schemas in a joint and an integrated manner is named as 'multistore' and 'polystore' in the database literature. In this paper, Entity Linking task is leveraged to transform texts into wellformed data and this data is managed by an integrated environment of different data models. Finally, this integrated big data environment will be queried and be examined by presenting the method.


Author(s):  
S. Sylvia Irish ◽  
M. Sicily Sherin ◽  
R. Surya ◽  
Y. Vidhya ◽  
Vidya Ramamoorthy

Author(s):  
Ashok Kumar J ◽  
Abirami S ◽  
Tina Esther Trueman

Sentiment analysis is one of the most important applications in the field of text mining. It computes people's opinions, comments, posts, reviews, evaluations, and emotions which are expressed on products, sales, services, individuals, organizations, etc. Nowadays, large amounts of structured and unstructured data are being produced on the web. The categorizing and grouping of these data become a real-world problem. In this chapter, the authors address the current research in this field, issues and the problem of sentiment analysis on Big Data for classification and clustering. It suggests new methods, applications, algorithm extensions of classification and clustering and software tools in the field of sentiment analysis.


2017 ◽  
Vol 39 (5) ◽  
pp. 177-202
Author(s):  
Hyun-Cheol Choi
Keyword(s):  
Big Data ◽  

Sign in / Sign up

Export Citation Format

Share Document