When will information retrieval be "good enough"?
By James Allan, Ben Carterette, Joshua Lewis. 2005
107 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Diane Kelly
- Alistair Moffat
- Mark Sanderson
- Leif Azzopardi
- Falk Scholer
- Andrew Turpin
- Justin Zobel
- Claudia Hauff
In Information Systems
- Mark Sanderson
- Alistair Moffat
- Diane Kelly
- Justin Zobel
- Leif Azzopardi
- Andrew Turpin
- Claudia Hauff
- Falk Scholer
Citations in the corpus
- Information Retrieval: A Biomedical and Health Perspective (2020, unknown): “[333] noted that only 2 of 25 RCTs where prior trials existed described the new results in the proper context of prior trials.”
- User performance versus precision measures for simple search tasks (2006, methodology): “Allan et al. [1] confirm this result (using bpref), but also show that for larger, specific increases in bpref, users do benefit on the instance recall task.”
- A comparison of user and system query performance predictions (2010, background): “However, there has been related work examining and perhaps challenging the relationship between system-centered retrieval effectiveness measures and actual user performance in traditional IR settings [1, 16, 28, 30].”
- Rank-biased precision for measurement of retrieval effectiveness (2008, background): “These issues are signi.cant, but al¨al¨they are separate from the topic of this article, and binary relevance judgments do provide a basis for assessing the utility of retrieval systems [Allan et al. 2005].”
- Test Collection Based Evaluation of Information Retrieval Systems (2010, background): “[6] studied the problem of locating relevant text fragments, called facets.”