Blog
Personalization
Modern recommender systems - Part 1: Introduction
How machine learning methods simplify item discovery and search.

Explaining Recommender Systems to Product Owners
In my presentation at the Data Technology Seminar organized by the European Brodcasting Union, I have focused on demonstrating that recommender systems can actually help public media organizations to better fulfill their role in society and reduce content distribution biases.

Inductive Matrix Completion: How to Improve Recommendations for Cold Start Users and Items by Incorporating Their Attributes
Matrix completion (MC), the problem of recovering the missing entries of a partially observed matrix, has found use in a wide range of domains. Still, its potentially most successful application is as a collaborative filtering technique for recommender systems (RSs)...

Breaking the News: The Role of AI in Modern Journalism
Artificial Intelligence (AI) has rapidly transformed the media industry in recent years. From automated news production to trend analysis and personalized content recommendations, AI has brought significant changes to the way media is created, distributed, and consumed.

Keeping Up With Digital Media Convergence
At Recombee, we felt the transition within the media industry accelerated by the pandemic. OTT and CTV consumption ballooned at a significant rate.

Real-Time Personalization of Content With AI-Powered Recommendations
Do you manage a publishing company, online gaming platform, or a streaming site with a content-heavy catalog and are thinking about how to improve the user experience?

Recombee Real-Time AI Recommendations as the New Destination in Segment
Segment has enabled its users to enjoy Recombee personalization services without the need to leave their platform and with minimum coding involved. With a few simple clicks, domains using Segment can upgrade their services to maximize the digital experience for their customers.

Recombee and Kentico Xperience: Guide to One-on-One Personalization
Recombee expanded its integration options - and now is available at the Kentico Xperience platform! Analyzing different types of personalization, we look into why Kentiko chose our AI-powered recommendation engine over manual segmentation.

Deep Learning for Recommender Systems: Next basket prediction and sequential product recommendation
Accurate “next basket prediction” will be enabling next generation e-commerce — predictive shopping and logistics. In this blogpost, we will discuss the deep learning technology behind next basket...

Evaluating Recommender Systems: Choosing the best one for your business
Together with the endless expansion of E-commerce and online media in the last years, there are more and more Software-as-a-Service (SaaS)…
The value of personalized recommendations for your business
The e-commerce boom makes online environment more competitive. Internet retailers seek competitive advantages and a personalized experience…

Artificial Intelligence in the Cloud
At Recombee, we “think big”, and prefer making big leaps in technology over taking small steps. Our team has been involved in data science and artificial intelligence research for many years. Beginning in 2012, we began to capitalize our knowledge and experience, developing products which…
