SENTIMENT ANALYSIS USING STRING TOKEN CLASSIFICATION ALGORITHM
| Main Authors: | Subramaniyaswamy, V, Harshaa, S, Padma Janani, M, Prabhalammbeka, BS |
|---|---|
| Format: | Journal PeerReviewed Book |
| Bahasa: | eng |
| Terbitan: |
http://www.ijpam.eu
, 2018
|
| Subjects: | |
| Online Access: |
http://eprints.rclis.org/33269/1/1211.pdf http://eprints.rclis.org/33269/ |
Daftar Isi:
- Sentiment analysis is a type of data mining which involves computation of opinions, sentiments and to determine if an information or a piece of text conveys positive, negative or neutral opinion. Public opinion regarding various aspects can be found using sentiment analysis. Clustering and classification are the key techniques in sentiment analysis. Consensus clustering is better than existing clustering algorithms as it provides a stable and efficient final result. However, it has its own drawbacks. Instead of performing consensus clustering and selecting classifiers from the consolidated result, we try to develop a new classification algorithm in our work