We Develop Global Recommendation Service and Share Our Insights Here
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.
Innovative Personalization Features for 2023
The digital world is changing; users' expectations for personalization are increasing, and our Recombee features are continuously improving. One of our focuses is to support our clients in providing the best possible user experiences...
Recombee Item Segmentations
Item Segmentations are Recombee's original and elegant solution to various advanced tasks related to hierarchical and relational data. The feature provides a flexible way to group items (products or pieces of content) into segments...
Bandit Models: Exploiting Popularity and Curiosity to Recommend Trending Content
Humans are inherently curious. In fact, curiosity is linked to the evolution of humankind. For instance, according to famous historian Yuval Noah Harari in his bestseller book "Sapiens", our language skills evolved as a way of gossiping...
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.
Recombee in E-mail Marketing: A Partner Success Story with Ryzeo
Do you feel there is a potential to increase your success with customers through an efficient recommender engine? You're highly likely right. Adding a recommender service to your emailing campaigns gives each client tailored product recommendations in all of their emails.
How We Are Using AI to Power Content Recommendations
In this article we walk you through how we are using the AI recommendation engine Recombee embedded in our headless CMS StoryBlok to drive content recommendations throughout our own website.
Visual and Interactive Evaluation of Recommender Systems
When building modern real-world artificial intelligence systems, it is increasingly important to validate that the system works correctly. This is however not an easy task. Existing tools for machine learning practitioners...
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?
AI-Powered Content Recommendations With a Headless CMS
Thanks to its API-first nature, it is quite straightforward to integrate your headless CMS with the most powerful AI-powered content recommendations available on the market. Luminary just did that with their own website, Kontent.ai and Recombee.
Making Linear Autoencoders Work for Large Scale Recommendation Systems
Linear autoencoders for collaborative filtering in recommender systems are simple and surprisingly accurate as we explained in our blogpost on how linear methods work. The critical disadvantage of methods like EASE is that they are not applicable to real-world problems...
New Features for a Better Personalization Experience
Like most of the world, the majority of 2021 was spent on home office or in isolation - which left us with all the time to be invested in work (and Netflix :) ) and improving UX for our clients. We are now happy to share new features we can offer to reach new levels of personalization.
Advancing Your Career in Artificial Intelligence with prg.ai and Recombee
At Recombee, we have always collaborated with academia — after all, five of our co-founders graduated from the Czech Technical University in Prague, one of the largest and oldest technical universities in Europe, and most of them hold a Ph.D. degree.
Linear Methods and Autoencoders in Recommender Systems
Linear regression is probably the simplest and surprisingly efficient machine learning method. It should be the method of your first choice, according to the famous KISS principle. Also, it often works better than sophisticated methods, because it is...
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.
Recombee in 2020: New Features and Improvements
We know that this year has been quite challenging for many people, including ourselves. However, today we want to focus entirely on the positive (no pun included) side of the year and the stuff we are the proudest of.
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...
How interdisciplinary collaboration can accelerate AI innovation
In a world where innovation is the new standard, Recombee uses the power of interdisciplinary collaboration to stay at the cutting edge of innovation. Partnering up with the leading player in the food industry (Bofrost) and academia (FIT CTU), allowed Recombee to hold a student competition to create AI which can shape the future of the food industry.
Introduction to personalized search
Personalized search should take into account user preferences and interactions of similar users. We combined search engine and recommender.
Recombee in 2019: New Features and Improvements
This year was really huge for us. We worked on new features so hard that we almost forgot to write a blog post about them :)
Check out our new client-side integration support and deploy personalized recommendations faster
We knew we had to bring something new to the table, when participating as a Beta Startup at Web Summit, the largest technology conference…
Machine Learning for Recommender systems — Part 2 (Deep Recommendation, Sequence Prediction, AutoML…
In the first part of our talk, we discussed basic algorithms, their evaluation and cold start problem. Below we show how deep learning…
Machine Learning for Recommender systems — Part 1 (algorithms, evaluation and cold start)
Recommender systems are one of the most successful and widespread application of machine learning technologies in business. There were many…
Migrating to Recombee from Microsoft Cognitive Services Recommendations
Microsoft has recently discontinued the Recommendations within the Azure Cognitive Services (MCSR). If you used this service, you are…
Personalized push notifications enabled by artificial intelligence
Recent progress in artificial intelligence enables us to design proactive AI systems. Whereas traditional recommender systems produce…
Personalized recommendations in 10 minutes
We have just released a video tutorial that will guide you through the integration of the Recombee recommendation service to your…
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…
Recommender systems explained
In this article, I overview broad area of recommender systems, explain how individual algorithms work.
Generating client libraries for Recombee recommendation API
Client libraries help programmers to integrate an API into their systems in a faster, easier and more readable way. We have recently published clients for Ruby and PHP, and we wish to provide clients for other major programming…
Personalized recommendations in Ruby
For those of you, who develop in Ruby, we prepared a simple client application enabling you to benefit from our personalized recommendations.
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…