User simulation for evaluating information access systems
With the emergence of various information access systems exhibiting increasing complexity,
there is a critical need for sound and scalable means of automatic evaluation. To address …
there is a critical need for sound and scalable means of automatic evaluation. To address …
[图书][B] Click models for web search
With the rapid growth of web search in recent years the problem of modeling its users has
started to attract more and more attention of the information retrieval community. This has …
started to attract more and more attention of the information retrieval community. This has …
Offline evaluation to make decisions about playlistrecommendation algorithms
Evaluating algorithmic recommendations is an important, but difficult, problem. Evaluations
conducted offline using data collected from user interactions with an online system often …
conducted offline using data collected from user interactions with an online system often …
A survey of query auto completion in information retrieval
F Cai, M De Rijke - Foundations and Trends® in Information …, 2016 - nowpublishers.com
In information retrieval, query auto completion (QAC), also known as typeahead [Xiao et al.,
2013, Cai et al., 2014b] and auto-complete suggestion [Jain and Mishne, 2010], refers to the …
2013, Cai et al., 2014b] and auto-complete suggestion [Jain and Mishne, 2010], refers to the …
Computationally efficient optimization of plackett-luce ranking models for relevance and fairness
H Oosterhuis - Proceedings of the 44th International ACM SIGIR …, 2021 - dl.acm.org
Recent work has proposed stochastic Plackett-Luce (PL) ranking models as a robust choice
for optimizing relevance and fairness metrics. Unlike their deterministic counterparts that …
for optimizing relevance and fairness metrics. Unlike their deterministic counterparts that …
Large-scale validation and analysis of interleaved search evaluation
Interleaving is an increasingly popular technique for evaluating information retrieval systems
based on implicit user feedback. While a number of isolated studies have analyzed how this …
based on implicit user feedback. While a number of isolated studies have analyzed how this …
Preference-based online learning with dueling bandits: A survey
In machine learning, the notion of multi-armed bandits refers to a class of online learning
problems, in which an agent is supposed to simultaneously explore and exploit a given set …
problems, in which an agent is supposed to simultaneously explore and exploit a given set …
Relative upper confidence bound for the k-armed dueling bandit problem
This paper proposes a new method for the K-armed dueling bandit problem, a variation on
the regular K-armed bandit problem that offers only relative feedback about pairs of arms …
the regular K-armed bandit problem that offers only relative feedback about pairs of arms …
Online evaluation for information retrieval
Online evaluation is one of the most common approaches to measure the effectiveness of an
information retrieval system. It involves fielding the information retrieval system to real users …
information retrieval system. It involves fielding the information retrieval system to real users …
Unifying online and counterfactual learning to rank: A novel counterfactual estimator that effectively utilizes online interventions
H Oosterhuis, M de Rijke - Proceedings of the 14th ACM international …, 2021 - dl.acm.org
Optimizing ranking systems based on user interactions is a well-studied problem. State-of-
the-art methods for optimizing ranking systems based on user interactions are divided into …
the-art methods for optimizing ranking systems based on user interactions are divided into …