Reuse in Question Answering: A Preliminary Study
Published 1 January 2003
Marc Light, Abraham Ittycheriah, Andrew Latto, Nancy McCracken
Citations8
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
A dozen categories of reuse that were found in usergenerated question sets are defined and exemplified and the corpus of question sets is discussed.
Abstract
People when asked a number of questions about a particular topic begin to become knowledgeable about the topic as they look for and find answers to the questions.
Keywords
Computer Science
Cambridge University Press eBooksCase-Based Reasoning
4,254 Citations2005Janet L. Kolodner
It is argued that CBR systems are easy to assess, develop, and deploy and can be evaluated in terms of their cost benefits and argued that CBR systems are easy to assess, develop, and deploy.
AI MagazineQuestion Answering from Frequently Asked Question Files: Experiences with the FAQ Finder System
339 Citations1997Robin Burke, Kristian J. Hammond +4 more
This technical report describes FAQ Finder, a natural language question answering system that uses files of frequently asked questions as its knowledge base, and describes the design and the current implementation of the system and its support components.
Overview of the Ninth Text REtrieval Conference (TREC-9).
80 Citations2000Ellen M. Voorhees, Donna Harman
Answering complex, list and context questions with LCC's Question-Answering Server
71 Citations2001Sanda M. Harabagiu, Dan Moldovan +8 more
The architecture of the Question-Answering server (QAS) developed at the Language Computer Corporation (LCC) and used in the TREC-10 evaluations is presented.
Lecture notes in computer scienceQuestion answering with Textual CBR
41 Citations1998Mario Lenz, André Hübner +1 more
This paper shows how case-based reasoning techniques can be applied to document retrieval, gives an overview over the approach to Textual CBR, describes a particular application project, and evaluates the performance of the system.
Gathering knowledge for a question answering system from heterogeneous information sources
36 Citations2001Boris Katz, Jimmy Lin +1 more
This work proposes an architecture for a collaborative question answering system that contains four primary components: an annotations system for storing knowledge, a ternary expression representation of language, a transformational rule system for handling some complexities oflanguage, and a collaborative mechanism by which ordinary users can contribute new knowledge by teaching the system new information.