Download - Aspect Based Sentiment Analysis
Aspect Based Sentiment Analysis
Aspect Based Sentimental analysis
DR. Asif Ekbal
Gaurav Kumar National Institute of Technology, Patna
Mentor :-
Summer Project
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Special ThanksTO
Shad Sir(Mentor)
2
Aspect Based Sentiments Analysis?
12/04/2016
312/04/2016
Our Objective
Stock Prediction
Flight Ranking
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A Working Example
12/10/2012
Sample InputVector
Labels for Input Vector
RNN Model
Results
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Example Continues
12/10/2012
Its BIO term we get for some testing data
Generated XML for Validation
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Annotator for SEMIEVAL -14
12/10/2012
What’s New ?
Use of RNN(Recurrent Neural Network)
BPTT(Back Propagation Through Time )
LSTM (Long Short Term Memory) Stochastic Gradient Desecnt
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Work Flow - 1
12/10/2012
Raw Review Annotation
Developed GUI for Annotation
Generated XML
Cohen’s Kappa AgreementResults
66 %
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Work Flow - 2
12/10/2012
Oh! Yes We got the data we
need Algorithms
Machine Learning
Supervised Learning
Supervised
Unsupervised
Reinforcement
ClassificationProblem
RegressionProblem
This is what our problem requires
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Final Work Flow
12/10/2012
• Classification Problem with fixed output Labels.
Annotated Text
Mathematical Representation
Word2Vector
Deep Learning
Recurrent Neural Network using DL4j
Results---Accuracy
BPTT
A bunch of Program t o bring data in format
Developed APITo Extract Aspect
Term
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Deep Learning4 Java Working
12/10/2012
• It is java Library to configure all types of Deep Learning Nets.• It has built-in GPU support.
» MAP-REDUCE PROCESS
» These Steps are Repeated untill we get minimum error.
INPUT DATA
1 2 3 4 NN-1
Weighted and Bias are Averaged
1 2 3 4 NN -1
Step 1
Clusters
Step 2
Weights are
Updated
Sample Code This is how we I am configuring
RNN
Fitting the Three
Dimension Input Vector
Training Starts Here
Results of Aspect Based Analysis
Trained on 1/3 data got the accuracy for Testing data
This accuracy is for Training data
Challenges to our approach
• Accuracy: Not 100 per cent
• A lot of Others terms: It means for extracting B-(beginning of Aspect term), I-(Intermediate Aspect Term), O(others). There is lot others terms. Even less than 1 percent belongs to B,I category and all 99 percent comes in O category.
• Need for lot of data: It seems like we required some more features from data to be more accurate.
Work Done During Internship Period
◎ Read the famous researchers and there Work.◎ Completed the Annotation of SEMIEVAL 14 about 5417 annotations.◎ Made GUI for Annotation of SEMIEVAL 14.◎ Completed the Annotation of SEMIEVAL 15-16 about 5417 annotations.◎ Program to Find N-grams ◎ Read some basic concepts of Deep Learning and its applications.◎ Implemented Recurrent Neural Network In Deep Learning4j.◎ Implemented code to Extract Aspect Term in RNN in Java.◎ Developed a API and a GUI for exacting Aspect Term.◎ Some other Basic Programs like XML generation,Word2Vector and many more.
◎ Self Implemented Works Are: -◎ Implemented Back propagation from Scratch in Java.◎ Implemented KNN, AutoEncoder etc in java.◎ Implemented to configure Neural Network using Feed Forward in Java from Scratch.◎ Implemented Linear Regression in Java from scratch.
Future Scope or Enhancement◎ We can provide more no of features in our data such as the
position of BIO terms as a feature.
◎ We can use Recursive Tensor Neural Network which works well for sentiments analysis and it is shown by Meta-Mind they have developed App on Twitter Sentiments Analysis.
◎ We need to extract some Outliers in our data.
◎ We can use Bootstrap Re-sampling of our Data.
◎ Any Suggestions Please Give !!!!!
Any Questions?