IRS13 Search Matching Functions chapter E. M. Keen Harvard University Gerard Salton Use, reproduction, or publication, in whole or in part, is permitted for any purpose of the United States Government. 111-30 using equations (1) and (2) already given; OVERLAP = 1+1+1+1+2 - 6 - Mm (12 , 39) - 12 - 0.50 COSINE = [OCRerr](i +2+1+1+1+3+1+2 )x(i +3+1 +[OCRerr] +2+1+3+7 +i +1+2 +3 +`5 +1+1+1+1+1 - [OCRerr](22X135) = 0.28 It should be noted that the overlap numerator uses the lowest w[OCRerr]ight assigned to a given matching concept in a request and a document; thus, for requests in which all the concepts are assigned a weight of 1 only, none o[OCRerr] the weighted concepts, in the document can exert any influence on the final correlation. In this situation, which is quite common for the requests tested, the weighted vector result is then identical to the unweighted result fQr overlap. For this reason, the con[OCRerr]arison of overlap and cosine was made using unweighted (logical) vectors; comparisons of the weighted versus unweighted (numeric versus logical) vectors will use the cosine correlation coefficient. Weighting achieved by manual or semi-manual decisions may also become a part of automatic retrieval systems of the future, under the assumption that such methods do not require large amounts of time and effort, and give useful improvements in performance. An example of this, using selec- tive request weighting to improve vital request notions, is given in section VIII. B) Retrieval Per[OCRerr]ormance Results Thirteen comparison runs on three collections are presented in Figure 17, evaluated by nox[OCRerr]nalized recall and normalized precision. All IRE-3 results show numeric to be superior to logical, and most the runs on Cran-1