Analytical Study on Algorithms for Content-Based Mobile Phone Recommendation System

Recommendation of anything helps in filtering out unwanted and irrelevant products from the entire work set which are not of any use or do not add any importance or value to the current task set to be accomplished. Mobile phone recommendation systems could be a probable revolution in the near future, as the telecommunication and mobile phone production industries are increasing exponentially in the market. Such systems would extract description of similar mobile phones which are most correlated with the mobile phone of user interest. The proposed system carries out this task taking the dataset which comprises of mobile phones and its features extracted from the e-commerce Web site ‘Flipkart’. The dataset comprises of 6917 records in total each one corresponding to a unique mobile phone in the Web site. The proposed model finds the similarities and does the predictions based on the input features in the dataset.