Incremental Learning on Sentiment Analysis Using Weakly Supervised Learning Techniques

Due to the advanced technologies of web 2.0, people are participating in and exchanging opinions through social media sites such as web forums and weblogs etc., classification and Analysis of such opinions and sentiment information is potentially important for both service and product providers, users because this analysis is used for making valuable decisions. Sentiment is expressed differently in different domains. Applying a sentiment classifiers trained on source domain does not produce good performance on target domain because words that occur in the train domain might not appear in the test domain.

Provided by: International Journal of Engineering, Science and Innovative Technology (IJESIT) Topic: Big Data Date Added: Mar 2014 Format: PDF

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