This document discusses aspect based sentiment analysis using recurrent neural networks. It describes annotating review data and developing a GUI for annotation. An API was created to extract aspect terms. A recurrent neural network model was implemented using Deeplearning4j with backpropagation through time to classify inputs. The system was trained on 1/3 of the data and achieved accuracy on the test data. Challenges included not reaching 100% accuracy and most terms being unrelated to aspects. Future work proposed using additional features and different neural network architectures.

1. Aspect Based Sentimental analysis
Aspect Based Sentiment Analysis
DR. Asif Ekbal
Gaurav Kumar
National Institute of Technology, Patna Mentor :-
Summer Project

2. 12/10/2012 Your footer here

3. Aspect Based Sentiments
Analysis?
12/04/2016 2

4. 12/04/2016 3
Our
Objective
Extract
Aspect
Term
API to Extract
Aspect Term

5. A Working Example
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Sample InputVector
Labels for Input
Vector
RNN Model
Results

6. Example Continues
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Its BIO term we
get for some
testing data
Generated XML
for Validation

7. Annotator for SEMIEVAL -14
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8. What’s New ?
Use of RNN(Recurrent Neural Network)
BPTT(Back Propagation Through Time )
LSTM (Long Short Term Memory)
Stochastic Gradient Desecnt

9. Work Flow - 1
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Raw
Review
Annotation
Developed GUI
for Annotation
Generated
XML
Cohen’s Kappa
AgreementResults
66 %

10. Work Flow - 2
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Oh! Yes We got
the data we
need Algorithms
Machine Learning
Supervised Learning
Supervised
Unsupervised
Reinforcement
Classification
Problem
Regression
Problem
This is
what our
problem
requires

11. Final Work Flow
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• 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 API
To Extract Aspect
Term

12. Deep Learning4 Java Working
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• 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

13. Sample Code
This is how we I
am configuring
RNN
Fitting the
Three
Dimension
Input Vector
Training Starts
Here

14. Results of Aspect Based Analysis
Trained on 1/3
data got the
accuracy for
Testing data
This accuracy is
for Training data

15. 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.

16. 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.

17. 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 !!!!!

18. Any Questions?