Generating SD-Rules in the SPECIALIST Lexical Tools - Optimization for Suffix Derivation Rule Set
Chris J. Lu, Destinee Tormey, Lynn McCreedy, Allen C. Browne · 2016
Suffix derivations (SDs) are used with query expansion in concept mapping as an effective Natural Language Processing (NLP) technique to improve recall without sacrificing precision. A systematic approach was proposed to generate derivations in the SPECIALIST Lexical Tools in which SD candidate rules were used to retrieve SD-pairs from the SPECIALIST Lexicon (Lu et al., 2012). Good SD candidate rules are gathered as SD-Rules in Lexical Tools for generating SDs that are not known to the Lexicon. This paper describes a methodology to select an optimized SD-Rule set that meets our requirement of 95\% system precision with best system performance from SD candidate rules. The results of the latest three releases of Lexical Tools show: 1) system precision and recall of selected SD-Rules are above 95\%. 2) a consistency between a computational linguistic approach and traditional linguistic knowledge for selecting the best Parent-Child rules. 3) a consistent approach yielding similar SD-Rule sets and system performance. Ultimately, it results in better precision and recall for NLP applications using Lexical Tools derivational related flow components.