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Cognitive Biases in Search: A Review and Reflection of Cognitive Biases in Information Retrieval
Conference on Human Information Interaction and Retrieval, 2021People are susceptible to an array of cognitive biases, which can result in systematic errors and deviations from rational decision making. Over the past decade, an increasing amount of attention has been paid towards investigating how cognitive biases ...
L. Azzopardi
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Generating Clarifying Questions for Information Retrieval
The Web Conference, 2020Search queries are often short, and the underlying user intent may be ambiguous. This makes it challenging for search engines to predict possible intents, only one of which may pertain to the current user.
Hamed Zamani +4 more
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Knowledge Graphs: An Information Retrieval Perspective
Foundations and Trends in Information Retrieval, 2020In this survey, we provide an overview of the literature on knowledge graphs (KGs) in the context of information retrieval (IR). Modern IR systems can benefit from information available in KGs in multiple ways, independent of whether the KGs are publicly ...
R. Reinanda, E. Meij, M. de Rijke
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From Matching to Generation: A Survey on Generative Information Retrieval
ACM Trans. Inf. Syst.Information Retrieval (IR) systems are crucial tools for users to access information, which have long been dominated by traditional methods relying on similarity matching.
Xiaoxi Li +6 more
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Bandit Algorithms in Information Retrieval
Foundations and Trends in Information Retrieval, 2019Bandit algorithms, named after casino slot machines sometimes known as “one-armed bandits”, fall into a broad category of stochastic scheduling problems. In the setting with multiple arms, each arm generates a reward with a given probability. The gambler’
D. Głowacka
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Information Retrieval: The Early Years
Foundations and Trends in Information Retrieval, 2019Information retrieval, the science behind search engines, had its birth in the late 1950s. Its forbearers came from library science, mathematics and linguistics, with later input from computer science.
D. Harman
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A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models
Knowledge Discovery and Data MiningAs one of the most advanced techniques in AI, Retrieval-Augmented Generation (RAG) can offer reliable and up-to-date external knowledge, providing huge convenience for numerous tasks.
Wenqi Fan +7 more
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The Power of Noise: Redefining Retrieval for RAG Systems
Annual International ACM SIGIR Conference on Research and Development in Information RetrievalRetrieval-Augmented Generation (RAG) has recently emerged as a method to extend beyond the pre-trained knowledge of Large Language Models by augmenting the original prompt with relevant passages or documents retrieved by an Information Retrieval (IR ...
Florin Cuconasu +7 more
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An Introduction to Neural Information Retrieval
Foundations and Trends in Information Retrieval, 2018Bhaskar Mitra, Nick Craswell
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