Picture this: your phone buzzes. It's your streaming app, and for once the notification is the one you actually wanted: "LIVE: your team just went 1–0 up, 78th minute”.
Personalization is never finished. Every change to your recommendation strategy raises new questions. Should you boost fresh content? Change used Logic? Introduce new filters?
The digital world continues to change at an incredible pace. As technology evolves and user expectations keep rising, creating experiences that feel relevant has never been more important.
In 2025, I became Head of Research at Recombee. I knew it would be a challenge: and I wasn’t wrong. Recombee is a leader in recommendation-as-a-service, with thousands of clients...
2025 marked 10 years of Recombee. A decade of building personalization from first principles, shaped by research, real-world deployments, and close collaboration with partners across industries.
In 2025, we focused on making advanced personalization easier to implement, scale, and maintain across products and platforms. Here’s a look at the key product updates we released last year.
Here’s what caught my attention in AI research lately, and where things might be heading in 2026. After 25+ years in this field, the pace has gotten hard to keep up with. I’m trying to make sense of...
Learning objectives of recommender systems and personalized search.
Personalization can be achieved without compromising user privacy. While many personalization systems have historically relied on practices now considered intrusive, like...
At Recombee, we don't just excel at recommendations – we provide powerful full-text search capabilities too. Our Quick, No-Code Search Widget exemplifies this, offering a seamless...
From ancient trade routes to modern urban planning, geography has consistently shaped human decisions and opportunities. Today, in the world of online business and personalized recommendations...
Imagine searching for "glass tubing" and getting recommendations for drug manufacturing equipment. As AI-powered search becomes ubiquitous — from online marketplaces to social networks...
As recommender systems become more widespread across digital platforms, concerns around fairness are coming to the forefront. Standard relevance-based ranking techniques, while effective...
This year is already off to an exciting start, and we’re rolling out new tools to improve efficiency and optimize recommendations. Here’s what’s available and what’s coming next.
When it comes to deciding between buying a recommender system and building one from scratch, the choice isn’t always straightforward. Both options come with their own set of pros and cons...
Why do influencers frequently request their subscribers to enable all notifications for their channels? This practice stems from their awareness that not all subscribers are regular...
Recombee has always been deeply connected to academia, with four of our six co-founders holding Ph.D. degrees. Over the years, our investment in research has grown alongside our company and the increasing demand for advanced features in the market.
In the fast-evolving world of recommender systems, understanding both how users interact with content and the actual content itself is crucial. Many existing recommender systems struggle to balance these two aspects...
Insights, the analytics section of our Admin UI, offers various predefined and fully customizable reports to track recommended items and how users interact with these recommendations.
The digital landscape and customer preferences and behavior are changing faster than ever now. To help our clients stay on top of the game, our team has focused on developing innovative features...
Data used by modern recommenders and how we can measure progress towards goals.
Picture this: you're on the hunt for the perfect new smartphone, browsing through your favourite online electronics store. The online store’s recommendation engine pops up with what it thinks could be your possible next gadget love...
Recombeelab, a joint research laboratory of Recombee and the Faculty of Information Technology at the Czech Technical University in Prague, experienced a highly productive year in 2023, publishing a series of insightful and impactful papers in the field of recommendation systems.
We look at the most interesting research directions and assess the state of knowledge in key areas of AI. We'll also estimate future developments in 2024 so you know what to prepare for.
Recommender systems and ethical controversies
In today's digital age, personalization has become the cornerstone of the media industry. Whether it's tailoring content recommendations, refining marketing strategies, or enhancing user experiences...
How machine learning methods simplify item discovery and search.
In my presentation at the Data Technology Seminar organized by the European Broadcasting 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.
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)...
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.
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...
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...
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...
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...
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...
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 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.
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...
We knew we had to bring something new to the table, when participating as a Beta Startup at Web Summit, the largest technology conference…
In the first part of our talk, we discussed basic algorithms, their evaluation and cold start problem. Below we show how deep learning…
Recommender systems are one of the most successful and widespread application of machine learning technologies in business. There were many…
Microsoft has recently discontinued the Recommendations within the Azure Cognitive Services (MCSR). If you used this service, you are…
Recent progress in artificial intelligence enables us to design proactive AI systems. Whereas traditional recommender systems produce…
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 e-commerce boom makes online environment more competitive. Internet retailers seek competitive advantages and a personalized experience…
In this article, I overview broad area of recommender systems, explain how individual algorithms work.
For those of you, who develop in Ruby, we prepared a simple client application enabling you to benefit from our personalized recommendations.
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…
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