Recent advances in sensor and mobile devices have enabled an unprecedented increase
in the availability and collection of urban trajectory data, thus increasing the demand for …

The data structure at the core of large-scale search engines is the inverted index, which is
essentially a collection of sorted integer sequences called inverted lists. Because of the …

Recent advancements in deep neural networks for graph-structured data have led to state-of-
the-art performance on recommender system benchmarks. However, making these methods …

This chapter provides an overview of the data matching process, and describes the five
major steps involved in this process: data pre-processing (cleaning and standardisation) …

The monograph Data Clustering: Theory, Algorithms, and Applications was published in
2007. Starting with the common ground and knowledge for data clustering, the monograph …

Latency and efficiency issues are often overlooked when evaluating IR models based on
Pretrained Language Models (PLMs) in reason of multiple hardware and software testing …

The rapid growth of the Web in the past two decades has made it the largest publicly
accessible data source in the world. Web mining aims to discover useful information or …

Pre-trained language models are increasingly important components across multiple
information retrieval (IR) paradigms. Late interaction, introduced with the ColBERT model …

As information retrieval researchers, we not only develop algorithmic solutions to hard
problems, but we also insist on a proper, multifaceted evaluation of ideas. The literature on …

Web search engines use highly optimized compression schemes to decrease inverted index
size and improve query throughput, and many index compression techniques have been …