Rauf Aliev's Books on Search & Recsys
Beyond English: Architecting Search for a Global World
Rauf Aliev
In a world where over half of all web content is non-English, most search systems are still built on a flawed, English-centric foundation. This "monolingual trap" leads to catastrophic failures in global markets, frustrating users and costing businesses dearly.
Beyond English is the definitive architect’s guide to escaping this trap. This book provides a comprehensive framework for designing and implementing search systems that are not just translated, but are linguistically and culturally fluent.
It moves from universal principles—like language detection, indexing pipelines, and query understanding—to deep, practical dives into the world's major language families.
Recommender Algorithms in 2026
Rauf Aliev
This book serves as an essential practitioner's guide to the world of recommender algorithms as it stands in early 2026. We begin with the indispensable baselines—from classic neighborhood models to powerful matrix factorization—and build toward the sophisticated deep learning architectures that power today's largest platforms, including hybrids for CTR prediction and state-of-the-art sequential models.
A core theme of this guide is the practical integration of the latest technological breakthroughs. We dedicate significant attention to the transformative impact of Large Language Models (LLMs), offering architectural blueprints for leveraging them as powerful semantic feature extractors, building reliable Retrieval-Augmented Generation (RAG) pipelines, and designing the next wave of generative and conversational recommender agents. Furthermore, we explore the critical role of multimodal models like CLIP for solving visual cold-start problems and provide insights into specialized areas like debiasing and fairness.
This is more than a survey; it is a toolkit for the modern engineer. Each section balances conceptual depth with pragmatic advice on implementation, scalability, and production readiness, making it the definitive resource for professionals tasked with creating value through personalization.
Inside Apache Solr and Lucene
How can you navigate the complex trade-offs between speed, memory consumption, and disk I/O when handling terabyte-scale data and thousands of concurrent users? This book dives deep into the core of Apache Solr and Lucene, offering answers from a system engineer's perspective. It explores the architectural decisions, data structures, and algorithms that enable these world-class search platforms to deliver exceptional performance and scalability, providing a blueprint for designing high-performance systems.
The insights in this book extend beyond the Solr and Lucene ecosystem. By using these platforms as a masterclass in pragmatic engineering, it offers valuable lessons for building any complex, data-intensive application. Their open-source codebases are a treasure trove of battle-tested solutions to universal challenges in concurrency, data partitioning, and distributed coordination. This book provides a curated tour of that treasure, distilling years of development and thousands of lines of code into core principles and patterns. It offers a unique opportunity to learn from the architectural choices of systems designed for immense scale and load, delivering invaluable lessons for system architects and engineers tasked with building resilient, high-performance software.
Buy on Amazon:
Designing E-commerce Search
Coming Soon: A deep dive into the specifics of designing and implementing search for e-commerce.