An Efficient Hotel Recommendation System

Objective

The objective of this project is to recommend the traveler’s the name of the best hotels based on their preferences, by analyzing the other traveler’s reviews together with the rating value to improve the prediction accuracy.

Project Overview

Nowadays, as the e-commerce industry is growing and becoming complex, everyone uses online websites for getting reviews and giving the reviews on the site in the form of review comments.Comment type varies from best level worst level.So to classify these comments or to predict the best outcome among the posted comments recommendation is needed. Recommend er System considers person’s opinion to identify their content more appropriately and selectively. This system applied to the various domain, but studies say that service-based recommendation system plays a significant role. In this decade, the growth rate of online hotel searching has been increased much faster and makes this online hotel searching a tough task due to the rich amount of online information.Reviews and comments written by the travelers replace the manual work but then to searching becomes the time-consuming task based on user preference.

People come to conclusions every day for some every question. “Which hotel should I see?” “Which item should I eat?”. People have many picks and but little time to explore there requirements. The technology advancement gives the different solutions to this type of problems. Although the availability of massive amount of data can be helpful, it can also make the managerial process more difficult. Users and customers have a lot of options to choose best possible and the most suitable item. It is essential to filter the information and personalize it for the use of each specific user. Recommend er systems used for making personalized suggestions of things to the users based on their requirements and preferences.

Proposed System

The proposed system introduces new hybrid recommendation approach by analyzing the user’s behavior using both textual content and rating data of user’s reviews. Mainly project focuses on building a Recommendation System based on hotel industry domain where traveler reviews will be mined to determine the sentiments of a traveler towards the hotel features which will help to analyze the user’s preference. Increasing the performance of recommendation is essential. So both rating of a hotel characteristics, as well as its sentiment orientation, considered. Also by collecting demographic information of the new user, the context-based hybrid recommendation will help to solve the issue of cold start problem. Rapid Miner is used to implement this recommendation system.

Features

The following list of features considered for recommending hotels to the customers.

• Food and drink
  • Coffee shop, tea, breakfast, lunch, dinner, fruit,varieties, bread.
• Location
  • Location, area, city, street, station, train, distance, bus, airport.
• Service and Infrastructure
  • Reception, Laundry, Dry cleaning,Cash withdrawal, Smoking area,service, front desk,luggage lobby.

 Software Requirements

• Windows OS
• RapidMiner

 Hardware Requirements

• Hard Disk – 1 TB or Above
• RAM required – 8 GB or Above
• Processor – Core i3 or Above

Technology Used

• Recommender System
• Data Mining
• Data Visualization