Given a sentence, return a score between 0 and 4, indicating the sentence's sentiment. 0 being very negative, 4 being very positive, 2 being neutral.
The engine uses the stanford CoreNLP library and the Scala binding gangeli/CoreNLP-Scala for parsing.
- initial version
$ python data/import_eventserver.py --access_key <your_access_key> --file data/train.tsv
The sample training data comes from https://www.kaggle.com/c/sentiment-analysis-on-movie-reviews. It is a tsv file. Each line contains 4 data, PhraseId, SentenceId, Phrase and Sentiment.
For example,
1 1 bad 1
$ pio build && pio train && pio deploy
The query takes a String s. The result contains a Double called sentiment.
normal:
$ curl -H "Content-Type: application/json" \
-d '{
"s" : "I am happy"
}' \
http://localhost:8000/queries.json \
-w %{time_connect}:%{time_starttransfer}:%{time_total}
{"sentiment":3.0714285712172384}0.005:0.027:0.027
$ curl -H "Content-Type: application/json" \
-d '{
"s" : "This movie sucks!"
}' \
http://localhost:8000/queries.json \
-w %{time_connect}:%{time_starttransfer}:%{time_total}
{"sentiment":0.8000000001798788}0.005:0.031:0.031
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