Tools and Technology: Python, Apache
Our client is the largest travel listings community worldwide – covering 8 million accommodations, airlines, restaurants, and experiences. They have 490 million unique visitors each month. They offer price comparison, worldwide holiday rental listings, free travel guides, popular forums and more.
Our client has been ranked as the most popular site for trip planning with millions of tourists visiting the site. As a result, the number of online reviews and opinions have been growing exponentially. To convert this data into actionable insights and to improve the quality of services and customer satisfaction, our client wanted to analyze sentiments of the customers receiving hospitality services on their trips.
Considering Cygnet’s expertise in AI and Machine Learning, the client partnered with Cygnet to develop and implement a next-gen Artificial Intelligence solution. After carefully understanding the project requirements, we proposed an effective method called Naive Bayes Classification to classify the polarity of reviews (negative, positive, conflict and neutral) given on the website and to score these reviews.