Have you ever wondered how online advertisement and the E-commerce industry works? Do you want to know more about the different recommender systems and which algorithms are used in recommender systems? Look no more as we have it all covered for you.
What is a recommender system?
The last few decades have shown a tremendous rise in web services like Netflix, YouTube, Amazon, etc. And with the rise of such sites, recommender systems are getting much more important than before. No matter if it’s related to E-commerce or online advertisements, the use of a recommender system is unavoidable by all means.
If defined in simpler words, a recommender system is basically an algorithm that is responsible for suggesting the relevant items to the consumers, which may include the movies to watch, what items to buy, which messages to read, etc.
If you are interested to learn more about algorithms and how to make them, check Algoexpert. What do I mean by that? Let me show you what I mean by introducing you to a lucrative Algoexpert discount of 20%!
Talking about movies, you may wonder about the biggest movie platform Netflix. If you wonder how does Netflix’s recommendation system work, here is how. Whenever you access Netflix, their recommendation system strives to help you find a series or movie that you can enjoy without putting in any effort.
The Netflix recommendation system estimates your likelihood of watching particular title or genre movies in their catalogue depending on these factors:
- Your viewing history and the way you rate other titles.
- According to the other members that have similar taste as you and their preference in Netflix’s service.
- Through the information about the tiles such as the genre they belong to, the actors, release years, categories, etc.
All of this information is collected by Netflix’s recommendation system and used as an input for the processing in algorithms. And your query of how does Netflix’s recommendation system work is answered.
Now that algorithm is finally discussed, lets now discuss how does recommendation algorithm work and which algorithms are used in the recommendation system.
Which algorithms are used in the recommendation system?
To answer your query of which algorithms are used in the recommendation systems and what are the different types of recommender systems, we have the list prepared for you. Here are the major algorithms used in the recommendation system:
Collaborative Filtering:
Collaborative filtering is basically an algorithm used in the recommendation system that basically makes the use of similarities between the items and users in order to provide the right recommendations.
This means this type of algorithm can provide a recommendation to user A depending on the interest of a similar user B. What makes collaborative filtering different is the fact the past user-item interaction is enough for the predictions to be made for similar users.
Content-Based Recommendations:
This solely depends on the choice of the users themselves, and the recommendations are made based on the items or products the users like based on their previous feedback or actions.
The content-based recommendations are less problematic for the new users as the items can be described by their characteristics or content, and thus relevant recommendations can be made for the new entities.
Context-Aware Recommendations:
The Context-Aware Recommendations (CAR) are said to generate better recommendations based on the specific contextual situation of the user. The CARs use several approaches to incorporate contextual information for the users in the recommendation process and then use such approaches for different applications.
These are the major and most common algorithms used in recommendation systems.
Hybrid Recommendations:
The hybrid approach of recommendations combines collaborative and content-based recommendations. These kinds of approaches are said to have provided better and accurate recommendations.
Netflix uses a hybrid approach of recommendations because it compares the watching habits of similar users and also offer movies that share the characteristics with all those films which the user has rated high.
How does Recommendation Algorithm work?
Now that your query of which algorithms are used in the recommendation system is answered let’s now move to how does recommendation algorithm work in specific. Here is how the recommendation algorithms work:
Collecting data:
The first step in order for the recommendation system to work is to collect data. The data can be either explicit or implicit.
- Explicit data includes the input of the data given by the users, such as their comments or ratings on various products.
- Implicit data includes order histories like page views, click-thru, search logs, cart histories, etc.
This kind of data is collected for every user that visits the site.
Storage of data:
The recommendations will get eventually better if more data is stored in the algorithms. You can use any kind of storage like a NoSQL database, standard SQL database, etc., depending on what you decide to store, i.e. either the user’s behaviour or inputs.
Analyzing the data:
In order to find items that are having similar data engagement, analyzing the data is extremely important. Here is how the analyzation is done:
- Real-time systems are used to analyze the data as it is.
- Through batch analysis, you can analyze and process the data periodically.
- The third option is near real-time analysis, which allows you to gather the data very quickly so you can easily refresh the analytics every few minutes or even seconds.
Filtering the data:
The next and final step is to filter the data and receive the relevant data so that relevant recommendations can be given to the users.
Which algorithms are used in the recommendation system? – Conclusion:
Now that the demand and use of recommendation systems are increasing day by day, there are different algorithms used by websites like YouTube, Netflix, Amazon, etc. These algorithms include content-based, collaborative filtering, context-based and the hybrid approach.
This article covered all your queries like which algorithms are used in the recommendation system, how does recommendation algorithm work, what are the different types of recommendation systems and how does Netflix’s recommendation system work to clear all your concepts about recommendation systems and stuff related to it.