Research Article

A Modular Efficiency Determination Formula for Information Retrieval Evaluations and Optimizations

Volume: 7 Number: 1 January 2, 2024
EN TR

A Modular Efficiency Determination Formula for Information Retrieval Evaluations and Optimizations

Abstract

The notion of efficiency has typically been associated with the efficiency of systems rather than users in Information Retrieval (IR) literature. In the usability literature, on the other hand, this notion is defined from a user-based perspective, corresponding to how long a user accomplishes a task. Despite this, the common aim for both has to do with the efficient use of time. This study examines the efficiency notion in the IR literature from a user-based efficiency window in the usability literature. In the present study, a modular efficiency determination formula (MEDEF) to create different efficiency indicators by focusing on IR system evaluations and optimizations from the usability perspective is proposed. The MEDEF can be thought of as an efficiency indicator creator based on both effectiveness metrics and efficiency indicators already used in IR studies. In the scope of this study, eight MEDEF-based efficiency indicators were created and compared to several baseline efficiency indicators already used in IR studies. While the study’s first aim is to reveal how consistent the MEDEF-based indicators are and whether these indicators are more successful/reliable than the baselines, the second is to set an example of the usage of efficiency indicators in evaluations of IR systems from a usability perspective. General findings from interactive user behaviour for one month show that the MEDEF-based indicators outperform the baseline indicators and further strengthen the reflections in the baseline indicators. Several usage scenarios regarding the potential of the MEDEF are also shared and discussed in the scope of the study.

Keywords

References

  1. Agichtein, E., Brill, E., & Dumais, S. (2006). Improving web search ranking by incorporating user behavior information. Proceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2006, 19-26. New York, New York, USA: ACM Press. https://doi.org/10.1145/1148170.1148177 google scholar
  2. Agichtein, E., Brill, E., Dumais, S., & Ragno, R. (2006). Learning user interaction models for predicting web search result preferences. Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR ’06, 3. New York, New York, USA: ACM Press. https://doi.org/10.1145/1148170.1148175 google scholar
  3. Alhabashneh, O., Iqbal, R., Doctor, F., & James, A. (2017). Fuzzy rule based profiling approach for enterprise information seeking and retrieval. Information Sciences, 394-395, 18-37. https://doi.org/10.1016/J.INS.2016.12.040 google scholar
  4. Arguello, J. (2014). Predicting search task difficulty. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Vol. 8416 LNCS (pp. 88-99). https://doi.org/10.1007/978-3-319-06028-6_8 google scholar
  5. Arkhipova, O., Grauer, L., Kuralenok, I., & Serdyukov, P. (2015). Search Engine Evaluation based on Search Engine Switching Prediction. Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 723-726. New York, NY, USA: ACM. https://doi.org/10.1145/2766462.2767786 google scholar
  6. Aula, A., Khan, R. M., & Guan, Z. (2010). How does search behavior change as search becomes more difficult? Proceedings of the 28th International Conference on Human Factors in Computing Systems - CHI ’10, 35. New York, New York, USA: ACM Press. https://doi.org/10.1145/1753326.1753333 google scholar
  7. Balakrishnan, V., & Zhang, X. (2014). Implicit user behaviours to improve post-retrieval document relevancy. Computers in Human Behavior, 33, 104-112. https://doi.org/10.1016/J.CHB.2014.01.001 google scholar
  8. Beierle, F., Aizawa, A., Collins, A., & Beel, J. (2020). Choice overload and recommendation effectiveness in related-article recommendations. International Journal on Digital Libraries, 21(3), 231-246. https://doi.org/10.1007/s00799-019-00270-7 google scholar

Details

Primary Language

English

Subjects

Software Engineering (Other)

Journal Section

Research Article

Publication Date

January 2, 2024

Submission Date

November 3, 2022

Acceptance Date

May 26, 2023

Published in Issue

Year 2023 Volume: 7 Number: 1

APA
Budak, V. Ö. (2024). A Modular Efficiency Determination Formula for Information Retrieval Evaluations and Optimizations. Acta Infologica, 7(1), 209-228. https://doi.org/10.26650/acin.1198925
AMA
1.Budak VÖ. A Modular Efficiency Determination Formula for Information Retrieval Evaluations and Optimizations. ACIN. 2024;7(1):209-228. doi:10.26650/acin.1198925
Chicago
Budak, Veli Özcan. 2024. “A Modular Efficiency Determination Formula for Information Retrieval Evaluations and Optimizations”. Acta Infologica 7 (1): 209-28. https://doi.org/10.26650/acin.1198925.
EndNote
Budak VÖ (January 1, 2024) A Modular Efficiency Determination Formula for Information Retrieval Evaluations and Optimizations. Acta Infologica 7 1 209–228.
IEEE
[1]V. Ö. Budak, “A Modular Efficiency Determination Formula for Information Retrieval Evaluations and Optimizations”, ACIN, vol. 7, no. 1, pp. 209–228, Jan. 2024, doi: 10.26650/acin.1198925.
ISNAD
Budak, Veli Özcan. “A Modular Efficiency Determination Formula for Information Retrieval Evaluations and Optimizations”. Acta Infologica 7/1 (January 1, 2024): 209-228. https://doi.org/10.26650/acin.1198925.
JAMA
1.Budak VÖ. A Modular Efficiency Determination Formula for Information Retrieval Evaluations and Optimizations. ACIN. 2024;7:209–228.
MLA
Budak, Veli Özcan. “A Modular Efficiency Determination Formula for Information Retrieval Evaluations and Optimizations”. Acta Infologica, vol. 7, no. 1, Jan. 2024, pp. 209-28, doi:10.26650/acin.1198925.
Vancouver
1.Veli Özcan Budak. A Modular Efficiency Determination Formula for Information Retrieval Evaluations and Optimizations. ACIN. 2024 Jan. 1;7(1):209-28. doi:10.26650/acin.1198925