What Should We Teach in Information Retrieval?

Author:

Markov Ilya1,de Rijke Maarten2

Affiliation:

1. University of Amsterdam , NJ, USA

2. University of Amsterdam

Abstract

Modern Information Retrieval (IR) systems, such as search engines, recommender systems, and conversational agents, are best thought of as interactive systems. And their development is best thought of as a two-stage development process: offline development followed by continued online adaptation and development based on interactions with users. In this opinion paper, we take a closer look at existing IR textbooks and teaching materials, and examine to which degree they cover the offline and online stages of the IR system development process. We notice that current teaching materials in IR focus mostly on search and on the offline development phase. Other scenarios of interacting with information are largely absent from current IR teaching materials, as is the (interactive) online development phase. We identify a list of scenarios and a list of topics that we believe are essential to any modern set of IR teaching materials that claims to fully cover IR system development. In particular, we argue for more attention, in basic IR teaching materials, to scenarios such as recommender systems, and to topics such as query and interaction mining and understanding, online evaluation, and online learning to rank.

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Management Information Systems

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. LoGE: an unsupervised local-global document extension generation in information retrieval for long documents;International Journal of Web Information Systems;2023-09-08

2. Implementation of English Digital Evaluation Model for Higher Vocational Colleges Based on Chaoxing Teaching Platform;2021 4th International Conference on Information Systems and Computer Aided Education;2021-09-24

3. The Search Studies Group at Hamburg University of Applied Sciences;Datenbank-Spektrum;2021-06-22

4. MergeDTS;ACM Transactions on Information Systems;2020-10-31

5. A Lightweight Environment for Learning Experimental IR Research Practices;Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval;2020-07-25

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