A MEDLINE categorization algorithm

The MEDLINE categorization algorithm (MCA) is based on semantic links existing between MeSH terms and metaterms on the one hand and between MeSH subheadings and metaterms on the other hand. These links are used to automatically infer a list of metaterms from any MeSH term/subheading indexing. Medical librarians manually select the semantic links.The MEDLINE categorization algorithm lists the medical specialties relevant to a MEDLINE file by decreasing order of their importance. The MEDLINE categorization algorithm is available on a Web site. It can run on any MEDLINE file in a batch mode. As an example, the top 3 medical specialties for the set of 60 articles published in BioMed Central Medical Informatics & Decision Making, which are currently indexed in MEDLINE are: information science, organization and administration and medical informatics.We have presented a MEDLINE categorization algorithm in order to classify the medical specialties addressed in any MEDLINE file in the form of a ranked list of relevant specialties. The categorization method introduced in this paper is based on the manual indexing of resources with MeSH (terms/subheadings) pairs by NLM indexers. This algorithm may be used as a new bibliometric tool.Categorization is designed to enhance resource description by organizing content description so as to enable the reader to grasp quickly and easily what a resource is about, what are the main topics discussed in it. In a previous study [1], we developed a categorization algorithm for health resources included in a quality-controlled health gateway called CISMeF (acronym of Catalogue and Index of Medical On-Line Resources in French) [2]. The relevance of the CISMeF Categorization Algorithm (CCA) was assessed on 123 randomly picked resources. The automatic categorization obtained was compared to the classified list of metaterms (or medical specialties) provided by a CISMeF librarian for each resource. The manual categorization was considered as the go