Title :
Sentiment miner: A prototype for sentiment analysis of unstructured data and text
Author :
Shahbaz, Muzammil ; Guergachi, A. ; ur Rehman, Rana Tanzeel
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Eng. & Technol., Lahore, Pakistan
Abstract :
This paper presents a method to apply opinion mining on unstructured text for polarity extraction and classification at sentence level within a document. The generation of massive unstructured information about individuals makes the task of progress tracking and monitoring almost impracticable which results in the quest to find some way for automated text analysis and tagging. The proposed solution in this work is the development of a System (Sentiment Miner). It will provide features to process and classify text files (reviews and appraisals) for opinion mining at sentence level using Natural language Processing techniques and Opinion Mining algorithms. The prototype of a final product; a Semantic Search Engine will facilitate in document retrieval for analysis whenever required.
Keywords :
data mining; information analysis; information retrieval; natural language processing; search engines; text analysis; Sentiment Miner system; document retrieval; natural language processing techniques; opinion mining; opinion mining algorithms; polarity classification; polarity extraction; semantic search engine; sentiment analysis; text analysis; text tagging; unstructured data analysis; Appraisal; Data mining; Feature extraction; Prototypes; Sentiment analysis; Speech; Tagging; Information Extraction (IE); Lexical Resources; Mining (TM); Natural Language Processing (NLP); Opinion Mining; SentiWordNet; Sentiment Analysis;
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2014 IEEE 27th Canadian Conference on
Conference_Location :
Toronto, ON
Print_ISBN :
978-1-4799-3099-9
DOI :
10.1109/CCECE.2014.6901087