We presented Machine Learning and Sentiment Word Net based method for opinion mining from hotel reviews and sentence relevance score based method for opinion summarization of hotel reviews. The classified and summarized hotel review information helps web users to understand review contents easily in a short time. Opinion Mining for Hotel Review system that detects hidden sentiments in feedback of the customer and rates the feedback accordingly. The system uses opinion-mining methodology in order to achieve desired functionality. Opinion mining for hotel reviews is a web application, which gives review of the feedback that is posted by various users. The system takes review of various users, based on the opinion, system will specify whether the posted hotel is good, bad, or worst. Based on users search on hotels, recommendations will be shown to the user based on how many times a user visited that particular hotel page. We use a database of sentiment based keywords along with positivity or negativity weight in database and then based on these sentiment keywords mined in user review is ranked. Once the user login to the system he views the hotels and gives review about the hotel. System will use database and will match the review with the keywords in database and rank the review accordingly. System will rate the hotel based on the rank of review. The role of the admin is to post new hotel and add keywords in database. This application is useful for those who are exploring new places and also useful for those who travel often. Using this application, a user will get to know which hotel is best and suitable for them. User can decide which hotel to accommodate before they reach the place.
- This system is useful for those people who visit new places quite often.
- People can easily decide whether the hotel is good or bad by using this application.
- Using Collaborative filtering, user will get recommendations of hotels.
- Since system ranks the feedback based on the weight age of the keywords in database, so the result is appropriate.
- User can decide which hotel to accommodate before they reach the place.
- System will match the opinion with those keywords which are in database rest of the words are ignored by the system
- It may provide inaccurate results if data entered incorrectly.