What is Recommendation System?
Recommendation system works on recommending products or services to the user based on his/her interest.
It compares one user with similar user and recommend products according to that. Recommendation system recommend, suggest the things to
the user according to their choices or according to previously taking actions which may effective reduces the time. Mainly, the companies
use recommender system to increase the sales and to get the customer's experience. Normally we can see every time when we search anything
to buy automatically, we get the details of all the most likely products in the market.
How recommendation system works: -
Recommendation system works on the aspects of Data collection and Data storage. What we search from the browser, recommendation
search engine collects all the data, store in their own memory. Search engine recommended the things to user after comparing with
the past searches so, the user get more effective and correct data with lesser time. After the storage, data recommendation system
required the filtering the data to get the accurate result or to make the final recommendations.
Two types of filtering performed by recommendation system is content filtering and collaborative filtering.
If a person read an article from a book and another article is from second book is also similar to the first one then recommendation system suggests to the user to read that book because now recommender knows the taste of the user. This type of filtering called the content filtering.
In collaborative filtering some techniques are required to find the relevant data let's suppose user A watches the three movies and user B watches the two movies but that two movies are common with user A. At that time recommender suggest to user B to watch the third movie which user A had already watched. From two movies recommender gets to know about the taste of the user and they already collects the previous data.
Examples of recommendation system: -
- Auto correction and predictions in keyboard is the common examples of recommendation system. When we type anything on
the keyboard recommender automatically suggest us the next upcoming word what it would be or what it would have to be. As well as this when we type anything wrong according to the recommender engine words library software correct it which may useful for us and which reduces the time.
- Had you ever received notification at your social site? “you may know his/her” or
“recommending friends requests” this all action is performed by the recommendation system.
software suggests us the friend's ID for making a connection by comparing both the friends list or by both the activities and
personal information like academics, address. Hobbies.
- Suggests products which is mostly likely by the users or to increase sales of that product on Amazon, flip kart and other e-commerce websites.
- Had you ever noticed? When you watch any video on you tube and Netflix, next time you can see automatically relevant videos related to first video or previously watched videos on home screen this all process is performed by recommendation system software.
- Songs recommendations in Spotify follows the same process. More applications are available which based on recommendation system and gives us the better result.
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