author = {Eric Knauss and Sebastian Meyer and Kurt Schneider},
  title = {{R}ecommending {T}erms for {G}lossaries: {A} {C}omputer-{B}ased {A}pproach},
  booktitle = {Proceedings of the First International Workshop on Managing Requirements
	Knowledge MARK '08},
  year = {2008},
  pages = {25-31},
  month = sep # { 8-8,},
  abstract = {Glossaries in Software Requirements Specifications (SRS) aim at establishing
	a common ground of definitions. However, ambiguous terms as due to
	tacit knowledge are seldom captured in glossaries. In addition, even
	if they are captured, they are seldom read, because potential readers
	are convinced that they already know how the term is defined. Such
	misunderstandings introduce high risks in projects - especially because
	they are so hard to detect. Therefore, a trigger is needed to start
	a discussion about these potentially dangerous terms. In this paper
	we show how context aware Requirements Engineering tools can heuristically
	detect these terms and point out the risk attached. We introduce
	two simple, yet powerful heuristics: Occurence counting detects important
	terms, comparison with old glossaries detects terms that others found
	worth defining in a glossary. Thus, we make use of glossaries from
	past projects to suggest possible terms of interest for current projects.
	Our approach was implemented and applied to six software projects.
	Based on these experiences we show the effectivity of our heuristics
	and how they could be used by learning organizations to reduce such
	ambiguity risks in their specific domain.},
  doi = {10.1109/MARK.2008.8}