Hi all, I just stumbled upon an article about natural language processing and sentiment analysis, a topic I'm interested in.
http://gigaom.com/2013/10/03/stanford-researchers-to-open-source-model-they-say-has-nailed-sentiment-analysis/ The idea they used seems to work for them well and is simple in its nature. When I've seen it, I immediately thought CLA (for its sequence learning ability) and CEPT (for the "ontological matrix" view on words). This combined should give interesting results and has a good (commercial) usecase. Tricky part would be training the classifier, getting some people to label the phrases (or some smart ways around this). Regards, Mark -- Marek Otahal :o)
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