#Recommendations as an #API: what is a Recommended System Nowadays?
What is an API?
An API is an application program interface which has determined routines, protocols, and tools for creating application. APIs are used to program interface components and they’re important because they provide the building blocks for making a program, which are then put together and completed by a given programmer. An API essentially makes the programmer’s job easier and less stressful.
Types of APIs
There are multiple kinds of APIs for different operating systems and for different purposes that suit the needs of different people. Let’s take Windows, which has several APIs that are used to run hardware systems and applications. The operating environment of most systems provide APIs and this allows programmers to create applications or programs that are compatible and consistent with the operating environment. Nowadays, however, there are websites that utilize APIs as well; for example, both Amazon and Ebay use APIs which allow programmers and developers to use existing retail infrastructure to create web stores. Also, third-party developers are able to use APIs on the web to solve problems with software for end-users.
There are many examples of APIs and the ProgrammableWeb tracks over 15 500 APIs. It also lists Google Maps, Twitter, Youtube, and Flickr as a few of the very most popular APIs.
SaaS is an acronym for software as a service recommender. These systems have several challenges and these include the handling of multi-tenancy. Multi-tenancy is a term for software architecture that allows a single instance of software to run on a server for multiple tenants, who are users that share access to software instance. SaaS Recommenders also process a large amount of data and they keep client’s data safe. Essentially, recommender systems work to filter data in order to determine the rating or preference a customer would give to an item. These systems are very common nowadays and they’re used in many areas of trade. There are recommender systems which are open-sourced, academic, media-centered, etc. It all depends on the niche you’re looking for!
Recommender systems work through collaborative filtering and content-based filtering. Collaborative filtering suggests items based on a client or visitor’s past used items and takes into consideration other users who chose similar items. This kind of filtering determines items that a user might be interested in. Content-based filtering, on the other hand, gives suggestions based on items with similar characteristics of a specific item so that the system can suggest items with similar properties.
The benefit of using SaaS Recommender Systems resides in your being able to pay for value with a low overhead instead of having a large upfront investment. SaaS Recommenders generally have a clear path to use and they provide with development and improvement as you use them. Below, you can find a list of Recommender Systems:
- Suggest Grid, which is the descendant of Rcmmdr, personalizes API for developers and recommends items based on the user’s previous items. The system uses collaborative filtering and allows visitors to see recommendations that they otherwise wouldn’t. Overall, it’s a generic system that is still highly suggested.
- Mortar Recommendation Engine is one that allows the programmer to create his or her own system through their PaaS Mortar and MongoDB’s. This system is used by MTV, Associated Press, etc. It’s made to be flexible, open, and portable.
- Peerius is focused on e-commerce focus for live and email recommendation. Like other systems, it works to personalize API and works with more the two hundred and fifty retailers. Individuals are exposed to product suggestions, messages, etc. and Peerius has been proven to increase sales.
There is also a nice list of such engines available to look at.
APIs are essential in web development; they’re an interface that specifies routines and commands that allow programmers to create programs. Above, you were introduced to APIs, different kinds of APIs and SaaS Recommenders.