ComputingComputer ScienceInformation SystemsDatabasesInformation RetrievalNatural Language ProcessingEvaluation Of Retrieval SystemsPersonalizationQuery ProcessingQuestion AnsweringHelp SystemsNatural Language ElicitationNatural Language InferencePreference RelationsUser Preference ModelingUser Preferences
Highly configurable software, such as web browsers,databases or office applications, have a large number of preferences that the user can customize, but documentation of them may be scarce or distributed. A user, tester or service technician may have to search through hundreds or thousands of choices in multiple documents when trying to identify which preference will modify a particular system behavior. In this paper we present PrefFinder, a natural language framework that finds (and changes) user preferences. It is tied into an application's preference system and static documentation. We have instantiated PrefFinder as a plugin on two open source applications, and as a stand-alone GUI for an industrial application. PrefFinder finds thecorrect answer between 76-96% of the time on more than 175 queries. When compared to asking questions on a help forum or through the company's service center, we can potentially save days or even weeks of time.
35
George A. Miller · Communications of the ACM · 1995 · 14.1K citations · Full text
Introduction to information retrieval
Choice Reviews Online · 2009 · 12.6K citations