Objective:
This dissertation developed an automatic classification procedure, as an example of a novel tool for an informationist, which extracts information from published abstracts, classifies abstracts into their fields of study, and then determines the researchers field of study and level of activity.
Method:
This dissertation compared a domain experts method of classification and an automatic classification procedure on a random sample of 101 medical researchers (derived from a potential list of 305 medical researchers) and their associated abstracts.
Design:
The study design is a retrospective, cross-sectional, inter-rater agreement study, designed to compare two classification methods (i.e., automatic classification procedure and domain expert). The study population consists of University of Pittsburgh, School of Medicine, Department of Medicine (DOM) professionals who (1) have published at least one article listed in PubMed® as first or last author and/or (2) are the primary investigator for at least one grant listed in CRISP.
Main outcome measures:
Three outcome measures were derived from the domain experts versus automatic categorization procedure: (1) an abstracts field of study, (2) a researchers field of study and (3) a researchers level of activity and field of study.
Results:
Kappa showed moderate agreement between automatic and domain expert classification for the abstracts field of study (Kappa = 0.535, n = 504, p < .000).
Kappa showed moderate agreement between automatic and domain expert classification of the researchers field of study (Kappa = 0.535, n = 101, p < .000). Kappa showed good agreement between automatic and domain expert classification of the researchers level of activity and field of study (Kappa = 0.634, n = 101, p < .000).
Conclusion:
The study suggests that an automatic library classification procedure can provide rapid classification of medical research abstracts into their fields of study. The classification procedure can also process multiple abstracts fields of study and classify their associated medical researchers into their field of study and level of activity and field of study. The classification procedure, used as a tool by an informationist, can be used as the basis for new services.
| Identifer | oai:union.ndltd.org:PITT/oai:PITTETD:etd-04302009-113137 |
| Date | 07 May 2009 |
| Creators | Cecchetti, Alfred A |
| Contributors | Robert A. Branch, MD, Ellen G. Detlefsen, DLS, Sherry Koshman, PhD, Toni Carbo, PhD |
| Publisher | University of Pittsburgh |
| Source Sets | University of Pittsburgh |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.library.pitt.edu/ETD/available/etd-04302009-113137/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Pittsburgh or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
Page generated in 0.0015 seconds