Deep metric learning to rank
We propose a novel deep metric learning method by revisiting the learning to rank
approach. Our method, named FastAP, optimizes the rank-based Average Precision …
approach. Our method, named FastAP, optimizes the rank-based Average Precision …
A theoretical analysis of NDCG type ranking measures
Ranking has been extensively studied in information retrieval, machine learning and
statistics. A central problem in ranking is to design a ranking measure for evaluation of …
statistics. A central problem in ranking is to design a ranking measure for evaluation of …
[图书][B] Information retrieval: Implementing and evaluating search engines
S Buttcher, CLA Clarke, GV Cormack - 2016 - books.google.com
An introduction to information retrieval, the foundation for modern search engines, that
emphasizes implementation and experimentation. Information retrieval is the foundation for …
emphasizes implementation and experimentation. Information retrieval is the foundation for …
Test collection based evaluation of information retrieval systems
M Sanderson - Foundations and Trends® in Information …, 2010 - nowpublishers.com
Use of test collections and evaluation measures to assess the effectiveness of information
retrieval systems has its origins in work dating back to the early 1950s. Across the nearly 60 …
retrieval systems has its origins in work dating back to the early 1950s. Across the nearly 60 …
Search result diversification
Ranking in information retrieval has been traditionally approached as a pursuit of relevant
information, under the assumption that the users' information needs are unambiguously …
information, under the assumption that the users' information needs are unambiguously …
Estimating average precision with incomplete and imperfect judgments
We consider the problem of evaluating retrieval systems using incomplete judgment
information. Buckley and Voorhees recently demonstrated that retrieval systems can be …
information. Buckley and Voorhees recently demonstrated that retrieval systems can be …
Evaluating diversified search results using per-intent graded relevance
Search queries are often ambiguous and/or underspecified. To accomodate different user
needs, search result diversification has received attention in the past few years. Accordingly …
needs, search result diversification has received attention in the past few years. Accordingly …
Dynamic link prediction by learning the representation of node-pair via graph neural networks
H Dong, L Li, D Tian, Y Sun, Y Zhao - Expert Systems with Applications, 2024 - Elsevier
Many real-world networks are dynamic, whose structure keeps changing over time. Link
prediction, which can foretell the emergence of future links, is one crucial task in dynamic …
prediction, which can foretell the emergence of future links, is one crucial task in dynamic …
Extending average precision to graded relevance judgments
SE Robertson, E Kanoulas, E Yilmaz - Proceedings of the 33rd …, 2010 - dl.acm.org
Evaluation metrics play a critical role both in the context of comparative evaluation of the
performance of retrieval systems and in the context of learning-to-rank (LTR) as objective …
performance of retrieval systems and in the context of learning-to-rank (LTR) as objective …
Metrics, statistics, tests
T Sakai - PROMISE winter school, 2013 - Springer
This lecture is intended to serve as an introduction to Information Retrieval (IR) effectiveness
metrics and their usage in IR experiments using test collections. Evaluation metrics are …
metrics and their usage in IR experiments using test collections. Evaluation metrics are …