A quantitative model for linking two disparate sets of articles in MEDLINE Export

@article{11083988073844878029related:zaowfG080pkJ, abstract = {Background: Identifying information that implicitly links two disparate sets of articles is a fundamental and intuitive data mining strategy that can help investigators address real scientific questions. The Arrowsmith two-node}, author = {Torvik, V. I. and Smalheiser, N. R.}, citeulike-article-id = {4415797}, citeulike-linkout-0 = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/23/13/1658}, day = {1}, issn = {1460-2059}, journal = {Bioinformatics}, keywords = {file-import-09-04-28}, month = {January}, pdf = {file://localhost/Users/hpiwowar/Documents/Papers/2007/Torvik/Bioinformatics\%202007\%20Torvik.pdf}, posted-at = {2009-04-28 16:00:55}, priority = {2}, title = {A quantitative model for linking two disparate sets of articles in MEDLINE}, url = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/23/13/1658}, year = {2007} }

TY - JOUR ID - 11083988073844878029related:zaowfG080pkJ L3 - citeulike-article-id:4415797 N2 - Background: Identifying information that implicitly links two disparate sets of articles is a fundamental and intuitive data mining strategy that can help investigators address real scientific questions. The Arrowsmith two-node JF - Bioinformatics SN - 1460-2059 TI - A quantitative model for linking two disparate sets of articles in MEDLINE KW - file-import-09-04-28 AU - Torvik, VI AU - Smalheiser, NR PY - 2007/01/01/ UR - http://bioinformatics.oxfordjournals.org/cgi/content/abstract/23/13/1658 ER -