Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Oleg Zendel"'
Publikováno v:
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.
Autor:
Oleg Zendel
Publikováno v:
SIGIR
The research on Query Performance Prediction (QPP) focuses on estimating the effectiveness of retrieval results in the absence of human relevance judgments. Accurately estimating the result of a search performed in response to a query has been extens
Publikováno v:
SIGIR
Accurately estimating the retrieval effectiveness of different queries representing distinct information needs is a problem in Information Retrieval (IR) that has been studied for over 20 years. Recent work showed that the problem can be significantl
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030721121
ECIR (1)
ECIR (1)
Query Performance Prediction (QPP) has been studied extensively in the IR community over the last two decades. A by-product of this research is a methodology to evaluate the effectiveness of QPP techniques. In this paper, we re-examine the existing e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0d05358f62f5775f509c8bcd6849cf9
https://doi.org/10.1007/978-3-030-72113-8_8
https://doi.org/10.1007/978-3-030-72113-8_8
Publikováno v:
CIKM
Online advertising systems often provide means for users to close ads and also leave feedback. Although closing ads requires additional user engagement and usually indicates a poor user experience, ad closes are not as scarce as one might expect. Rec
Publikováno v:
SIGIR
The query performance prediction (QPP) task is to estimate the effectiveness of a search performed in response to a query with no relevance judgments. Existing QPP methods do not account for the effectiveness of a query in representing the underlying