SP500215 Appendix B: System Features Appendix National Institute of Standards and Technology D. K. Harman CONSThUCTION OF INDICES, KNOWI£DCE BASES, AND O¶HER DATA SThUCTUBES MEIHODS USED Lc" document weights for dortVI, "1sp" document weights for dortPl, Sr," document weights for dort[OCRerr], dort12 Sr," query regression query weights for dort[OCRerr] Inn" query weights for dort12 [OCRerr]y pair of adjacent non stopwords that occur 25 times in Dl. !odified lovin's Algorithm. tc" document weights for adhoc and routing. tc" documents weights for adhoc. occhio baeed feedback query weights for routing [OCRerr]ights determined from various frequency statistics by logistic regression. [OCRerr]ause we used the UMASS INQUERY system and its indexing, all of the answers to the questions in this section for our systems are identical to those for th[OCRerr] )ocument vectors use "inc" weights suggested by Buckley et al. in TREC-l Proceedings: weight of a term is proportional to its frequency in that document and osine factor. Query vectors use `Yltn" weights: term frequency factor multiplied by inverse document frequency factor. Original query terms normalized 1" ormalization; additional terms normalized by the length of the original terms. )0ne by hand when selecting synsets to add to topic text. [OCRerr]gt = 0.5 + 0.5 * tfhnax[OCRerr]tf(doc). SMART "ann" weighting. ource text preparsed into SMART format before being processed by SMART according to above p&amete[OCRerr]