Papers by Prathusha Kameswara Sarma

1 papers
Learning Word Embeddings for Data Sparse and Sentiment Rich Data Sets (N18-4)

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Challenge: Existing word embeddings for sentiment analysis are limited in domain specific applications . generic word embeds are poor initialization for tasks on domain specific data sets.
Approach: They propose to use word embeddings adapted for domain specific data sets in sentiment classification applications.
Outcome: The proposed algorithms learn word embeddings on sparse and sentiment rich data sets.

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