Determining the effectiveness of retrieval algorithms

By Hans-Peter Frei, P. Schäuble. 1991

Subfields: Information Retrieval & Search, Evaluation & Benchmarks

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Retrieval & Search

1. Mark Sanderson
2. C. Clarke
3. Jimmy J. Lin
4. Ellen M. Voorhees
5. Mark D. Smucker
6. Cheng-hsin Luo
7. Alexandra Vtyurina
8. Nick Craswell

In Evaluation & Benchmarks

1. Mark Sanderson
2. C. Clarke
3. Nick Craswell
4. Mark D. Smucker
5. Cheng-hsin Luo
6. Alexandra Vtyurina
7. Xinyi Yan
8. Ellen M. Voorhees

Citations in the corpus

• Human Preferences as Dueling Bandits (2022, background): “Proposals to base information retrieval evaluations on preference judgments date back to the early 1990s [15, 30, 37].”
• Test Collection Based Evaluation of Information Retrieval Systems (2010, background): “Although not the first measure to consider preference — see Frei and Schäuble’s usefulness measure [88] — BPref is the first commonly used measure to which preference judgments could be easily applied.”
• Assessing Top- Preferences (2020, background): “Frei and Schäuble [16] also sidestep absolute relevance in favor of relative comparisons between items, arguing that human assessors make relative comparisons more easily and consistently.”
• Evaluation Measures Based on Preference Graphs (2021, background): “Preferences have a long history as an alternative to graded relevance judgments, extending back to the early 1990’s[16, 23].”