Aspect Based Sentiment Analysis

Aspect Based Sentimental analysis

DR. Asif Ekbal

Gaurav Kumar National Institute of Technology, Patna

Mentor :-

Summer Project

Your footer here12/10/2012

Special ThanksTO

Shad Sir(Mentor)

2

Aspect Based Sentiments Analysis?

12/04/2016

312/04/2016

Our Objective

Stock Prediction

Flight Ranking

Your footer here

A Working Example

12/10/2012

Sample InputVector

Labels for Input Vector

RNN Model

Results

Your footer here

Example Continues

12/10/2012

Its BIO term we get for some testing data

Generated XML for Validation

Your footer here

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

Your footer here

Work Flow - 1

12/10/2012

Raw Review Annotation

Developed GUI for Annotation

Generated XML

Cohen’s Kappa AgreementResults

66 %

Your footer here

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

Your footer here

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

Your footer here

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?