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Semantic Question Pair Matching with Deep Learning

Sample Question Pair in Quora

Quora Dataset

Distribution of Questions

Distribution of Questions

System Architecture System Architecture

Stopwords Removal

Stopwords Removal

Stemming | Lemmatization

Stemming

Lemmatization

Word2vec

Word2vec

Correlation Heatmap for features

Heatmap

Distribution Plots

len_q1 vs len_q2 diff_len
len_q1 vs len_q2 diff_len

Scatter Plots

cosine_distance vs common_words fuzz_partial_ratio vs common_words

Supervised Machine Learning Models

S.N. Supervised Machine Learning Accuracy
1 Random Forest 0.7235
2 K Nearest Neighbors 0.7104
3 Logistic Regression 0.6680

Neural Network

Neural Network

Training Neural Network

Training of Network

S.N. Learning Rate Batch Size Training Accuracy
1 0.01 30 0.6264
2 0.005 30 0.6938
3 0.001 30 0.7256
Training Loss Training Accuracy ROC
Training Loss Training Accuracy ROC

Confusion Matrix

Predicted
0 1
Actual 0 36462 12792
0 8954 20455

Some Metrics

Measure Value Derivations
Sensitivity 0.6955 TPR = TP / (TP + FN)
Specificity 0.7403 SPC = TN / (FP + TN)
Precision 0.6152 PPV = TP / (TP + FP)
Negative Predictive Value 0.8028 NPV = TN / (TN + FN)
False Positive Rate 0.2597 FPR = FP / (FP + TN)
False Discovery Rate 0.3848 FDR = FP / (FP + TP)
False Negative Rate 0.3045 FNR = FN / (FN + TP)
Accuracy 0.7236 ACC = (TP + TN) / (P + N)
F1 Score 0.6529 F1 = 2TP / (2TP + FP + FN)

Flask Interface

Home

Evaluate

Lookups

Install essential libraries

pip3 install numpy
pip3 install fuzzywuzzy
pip3 install gensim
pip3 install python-Levenshtein
pip3 install sklearn
pip3 install pyemd
pip3 install keras
pip3 install tensorflow

Download Models from https://drive.google.com/open?id=1YgibRxIBRPDBvrPPstxkInnNKc6M5lFc & Extract to ./semantic-question-matching/flask_interface/

cd ./semantic-question-matching/flask_interface

export FLASK_APP=app.py

flask run --without-threads