Name
Abstract | ||
|---|---|---|
With recent development of Web 2.0 and Natural Language Processing, use of regional languages is also grown for communication. In India people express their views by using mother tongue such as Hindi, Bengali, Kannada, Marathi etc. As Hindi is fourth most spoken language in the world therefore many researchers are working on Hindi Sentiment Analysis. Sentiment Analysis is natural language processing task that mine information from various text forms such as blogs, reviews and classify them on basis of polarity as positive, negative or neutral. A speech is combination of variety of topics. So there is requirement for classifying given Hindi speech document in to different classes and then extract sentiments in terms of positive, negative and neutral for identified classes. In this paper we have proposed a model for classification of Hindi speech documents into multiple classes with the help of ontology. Further, sentiment analysis is carried out using HindiSentiWordNet (HSWN) to determine the polarity of individual class. To improve accuracy of polarity extraction result we have combined HSWN and LMClassifier. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICACCI.2016.7732097 | 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI) |
Keywords | Field | DocType |
Sentiment Analysis,Ontology,HindiSentiWordNet (HSWN),LMClassifier | Ontology,Computer science,Hindi,Sentiment analysis,Bengali,Artificial intelligence,Natural language processing,Marathi,Spoken language,First language,Multiclass classification | Conference |
ISBN | Citations | PageRank |
978-1-5090-2030-0 | 0 | 0.34 |
References | Authors | |
5 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sumitra Pundlik | 1 | 0 | 0.34 |
| Prasad Dasare | 2 | 0 | 0.34 |
| Prachi Kasbekar | 3 | 0 | 0.34 |
| Akshay Gawade | 4 | 0 | 0.34 |
| Gajanan Gaikwad | 5 | 0 | 0.34 |
| Purushottam Pundlik | 6 | 0 | 0.34 |