Comparing retrieval performance in online data bases

摘要

This study systematically compares retrievals on 11 topics across five well-known data bases, with MEDLINE's subject indexing as a focus. Each topic was posed by a researcher in the medical behavioral sciences. Each was searched in MEDLINE, EXCERPTA MEDICA, and PSYCINFO, which permit descriptor searches, and in SCISEARCH and SOCIAL SCISEARCH, which express topics through cited references. Searches on each topic were made with (1) descriptors, (2) cited references, and (3) natural language (a capability common to all five data bases). The researchers who posed the topics judged the results. In every case, the set of records judged relevant was used to calculate recall, precision, and novelty ratios. Overall, MEDLINE had the highest recall percentage (37%), followed by SSCI (31%). All searches resulted in high precision ratios; novelty ratios of data bases and searches varied widely. Differences in record format among data bases affected the success of the natural language retrievals. Some 445 documents judged relevant were not retrieved from MEDLINE using its descriptors; they were found in MEDLINE through natural language or in an alternative data base. An analysis was performed to examine possible faults in MEDLINE subject indexing as the reason for their nonretrieval. However, no patterns of indexing failure could be seen in those documents subsequently found in MEDLINE through known-item searches. Documents not found in MEDLINE primarily represent failures of coverage—articles were from nonindexed or selectively indexed journals. Recommendations to MEDLINE managers include expansion of record format and modification of journal and article selection policies.