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Evaluating and analyzing click simulation inweb search. / Malkevich, Stepan; Markov, Ilya; Michailova, Elena; De Rijke, Maarten.

ICTIR 2017 - Proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval. Association for Computing Machinery, 2017. p. 281-284.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Malkevich, S, Markov, I, Michailova, E & De Rijke, M 2017, Evaluating and analyzing click simulation inweb search. in ICTIR 2017 - Proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval. Association for Computing Machinery, pp. 281-284, 7th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2017, Amsterdam, Netherlands, 1/10/17. https://doi.org/10.1145/3121050.3121096

APA

Malkevich, S., Markov, I., Michailova, E., & De Rijke, M. (2017). Evaluating and analyzing click simulation inweb search. In ICTIR 2017 - Proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval (pp. 281-284). Association for Computing Machinery. https://doi.org/10.1145/3121050.3121096

Vancouver

Malkevich S, Markov I, Michailova E, De Rijke M. Evaluating and analyzing click simulation inweb search. In ICTIR 2017 - Proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval. Association for Computing Machinery. 2017. p. 281-284 https://doi.org/10.1145/3121050.3121096

Author

Malkevich, Stepan ; Markov, Ilya ; Michailova, Elena ; De Rijke, Maarten. / Evaluating and analyzing click simulation inweb search. ICTIR 2017 - Proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval. Association for Computing Machinery, 2017. pp. 281-284

BibTeX

@inproceedings{2953a2e35ff84b41b2987a27878417c7,
title = "Evaluating and analyzing click simulation inweb search",
abstract = "We evaluate and analyze the quality of click models with respect to their ability to simulate users' click behavior. To this end, we propose distribution-based metrics for measuring the quality of click simulation in addition to metrics that directly compare simulated and real clicks. We perform a comparison of widely-used click models in terms of the quality of click simulation and analyze this quality for queries with different frequencies. We find that click models fail to accurately simulate user clicks, especially when simulating sessions with no clicks and sessions with a click on the first position. We also find that click models with higher click prediction performance simulate clicks better than other models.",
author = "Stepan Malkevich and Ilya Markov and Elena Michailova and {De Rijke}, Maarten",
year = "2017",
month = oct,
day = "1",
doi = "10.1145/3121050.3121096",
language = "English",
pages = "281--284",
booktitle = "ICTIR 2017 - Proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval",
publisher = "Association for Computing Machinery",
address = "United States",
note = "7th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2017 ; Conference date: 01-10-2017 Through 04-10-2017",

}

RIS

TY - GEN

T1 - Evaluating and analyzing click simulation inweb search

AU - Malkevich, Stepan

AU - Markov, Ilya

AU - Michailova, Elena

AU - De Rijke, Maarten

PY - 2017/10/1

Y1 - 2017/10/1

N2 - We evaluate and analyze the quality of click models with respect to their ability to simulate users' click behavior. To this end, we propose distribution-based metrics for measuring the quality of click simulation in addition to metrics that directly compare simulated and real clicks. We perform a comparison of widely-used click models in terms of the quality of click simulation and analyze this quality for queries with different frequencies. We find that click models fail to accurately simulate user clicks, especially when simulating sessions with no clicks and sessions with a click on the first position. We also find that click models with higher click prediction performance simulate clicks better than other models.

AB - We evaluate and analyze the quality of click models with respect to their ability to simulate users' click behavior. To this end, we propose distribution-based metrics for measuring the quality of click simulation in addition to metrics that directly compare simulated and real clicks. We perform a comparison of widely-used click models in terms of the quality of click simulation and analyze this quality for queries with different frequencies. We find that click models fail to accurately simulate user clicks, especially when simulating sessions with no clicks and sessions with a click on the first position. We also find that click models with higher click prediction performance simulate clicks better than other models.

UR - http://www.scopus.com/inward/record.url?scp=85033236658&partnerID=8YFLogxK

U2 - 10.1145/3121050.3121096

DO - 10.1145/3121050.3121096

M3 - Conference contribution

AN - SCOPUS:85033236658

SP - 281

EP - 284

BT - ICTIR 2017 - Proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval

PB - Association for Computing Machinery

T2 - 7th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2017

Y2 - 1 October 2017 through 4 October 2017

ER -

ID: 38401093