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 …

Information retrieval (IR) has changed considerably in recent years with the expansion of the
World Wide Web and the advent of modern and inexpensive graphical user interfaces and …

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 …