Relevance odds of retrieval overlaps from seven search fields
dc.contributor.author | Pao, Miranda Lee | en_US |
dc.date.accessioned | 2006-04-10T18:11:30Z | |
dc.date.available | 2006-04-10T18:11:30Z | |
dc.date.issued | 1994 | en_US |
dc.identifier.citation | Pao, Miranda Lee (1994)."Relevance odds of retrieval overlaps from seven search fields." Information Processing & Management 30(3): 305-314. <http://hdl.handle.net/2027.42/31615> | en_US |
dc.identifier.uri | http://www.sciencedirect.com/science/article/B6VC8-469V2FJ-3R/2/9b2ae54861abe25a6c5d05fe391069aa | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/31615 | |
dc.description.abstract | Data contained in a 1982 paper were analyzed in terms of relevance odds of common items retrieved by searching any two content-bearing search fields. While the 1982 study compared the relative retrieval performance of 7 search fields, the present study shows that duplicate documents retrieved by the use of terms from any two of the fields would have higher odds of being judged relevant than those retrieved by only one of the fields. Sixty-three relevance odds were computed using the log cross product technique. The highest relevance odds were associated with common items retrieved from assigned descriptors and from truncated free-text terms from either the title or abstract fields; their relevance odds were 19 to 2 in favor of overlaps. Overlap retrieval could be considered a strategy for high precision searching. | en_US |
dc.format.extent | 874701 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Elsevier | en_US |
dc.title | Relevance odds of retrieval overlaps from seven search fields | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Information and Library Science | en_US |
dc.subject.hlbsecondlevel | Computer Science | en_US |
dc.subject.hlbtoplevel | Humanities | en_US |
dc.subject.hlbtoplevel | Social Sciences | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | School of Information and Library Studies, University of Michigan, Ann Arbor, MI, U.S.A. | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/31615/1/0000546.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1016/0306-4573(94)90046-9 | en_US |
dc.identifier.source | Information Processing & Management | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.