Natural Language Processing (NLP) to classify service review

Natural language processing (NLP) is a field of computer science, artificial intelligence and computational linguistics. Furthermore, it is concerned with the interactions between computers and human (natural) languages. Hence, it is concerned with programming computers to fruitfully process large natural language corpora. Challenges in natural language processing frequently involve understanding and generation of natural language.

In natural language processing, Latent Dirichlet Allocation (LDA) is a generative statistical model. It allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar. For example, if observations are words collected into documents, it posits that each document is a mixture of a small number of topics and that each word’s creation is attributable to one of the document’s topics.

When talking about the area of opinion analysis, the common misconception is that it is all about trying to predict the polarity of a piece of ‘opinion text’ as being positive or negative. Studies are made the task of sentiment polarity prediction, but the area of opinion analysis is actually much broader than just that. Many of the tasks related to opinion analysis often go unnoticed due to lack of ‘popularity’. Some interesting tasks related to opinion analysis are:

1)Subjectivity Detection
2)Sentiment Prediction
3)Aspect Based Sentiment Summarization
4)Constrastive Viewpoint Summarization

Executive Summary: Categorize Customer feedback in positive or negative using Natural Language Processing.

Problem Statement: Our US Client was looking for automated solution to classify reviews posted on multiple social networking
channels they monitor about their service.

Solution Description: We developed a machine learning neural network based naive bayes classifier to classify the service
review received on their social network sites.

Front end: HTML and Jquery

Backend: Python, Machine Learning Algorithms, Naive Bayes Classifier, Neural Network

Results Achieved: Automated, reliable, high accuracy, solution to categorize service review implemented improving time to analyze and respond to client feedback.