
About this book series
Information Retrieval (IR) deals with access to and search in mostly unstructured information, in text, audio, and/or video, either from one large file or spread over separate and diverse sources, in static storage devices as well as on streaming data. It is part of both computer and information science, and uses techniques from e.g. mathematics, statistics, machine learning, database management, or computational linguistics. Information Retrieval is often at the core of networked applications, web-based data management, or large-scale data analysis.
The Information Retrieval Series presents monographs, edited collections, and advanced text books on topics of interest for researchers in academia and industry alike. Its focus is on the timely publication of state-of-the-art results at the forefront of research and on theoretical foundations necessary to develop a deeper understanding of methods and approaches.This series is abstracted/indexed in EI Compendex and Scopus.
- Electronic ISSN
- 2730-6836
- Print ISSN
- 1871-7500
- Series Editor
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- ChengXiang Zhai,
- Maarten de Rijke
Book titles in this series
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Learning to Quantify
- Authors:
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- Andrea Esuli
- Alessandro Fabris
- Alejandro Moreo
- Fabrizio Sebastiani
- Open Access
- Copyright: 2023
-
A Behavioral Economics Approach to Interactive Information Retrieval
Understanding and Supporting Boundedly Rational Users
- Authors:
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- Jiqun Liu
- Copyright: 2023
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Data Science for Fake News
Surveys and Perspectives
- Authors:
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- Deepak P
- Tanmoy Chakraborty
- Cheng Long
- Santhosh Kumar G
- Copyright: 2021
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Abstracted and indexed in
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- DBLP
- EI Compendex
- Norwegian Register for Scientific Journals and Series
- SCOPUS
- zbMATH