<?xml version="1.0" standalone="yes"?>
<Paper uid="P85-1029">
  <Title>DESCRIPTION STR.ATEGIE.S FOR NAIVE AND EXPERT USERS</Title>
  <Section position="3" start_page="0" end_page="0" type="intro">
    <SectionTitle>
INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> Whether the purpose of a natural language program Ls to ease man-machine interactions \[Kaplan 82; Hayes and Reddy 79\] or to model human communication ~Lehnert 781, it must take into conslder~tion certain characteristics of the person engaged in the interaction. \[n an interaction between people, the goals, beliefs, retentions, knowledge and past experience of the participants will play a role in how they communicate with each other \[Cohen and Perrault 791, \[Perrault and Allen 80\[. Similarly, those characteristics should play a role in the way a computer system interacts with a user. In particular, a questlon-answering program that provides access to a large amount of data to many different users will be most useful if it can tailor its answers to each user.</Paragraph>
    <Paragraph position="1"> We are interested here in how the level of knowledge (or expertise) of the user a~fects an answer.</Paragraph>
    <Paragraph position="2"> As an example of this kind of tailoring in a naturally occurring conversation, an explanation of how a car engine works a~med a~ ~ child wdl be different than one ~med ~tt an adult, and an explanation adequate for a music student is probably not quite sufficient for a student in mechanic~l engineering. \[n this paper, we study the strategies used tn natural language to describe physical objects to two different types of users: naive and expert. By naive ~nd expert, we refer to how familiar a user m about the domain of the database as opposed to how experienced the user is with the question/aJnswering system. When the database ts complex, it becomes important to vary the level and the kind of details included in the answer in order to provide an answer that caa be best understood by the user.</Paragraph>
    <Paragraph position="3"> We plan to use this distinction in the question-answering program for RESEARCHER, a system being developed at Columbia University. RESEARCHER reads, remembers, and generalizes from patents abstracts written in English \[Lebowitz 83\]. The abstracts descrlbe complex physical objects in which spatial and functional relations are important. Thus, we are interested in characterizing spatial strategies that can be used for experts and novices about certmn physical obiects. We give deta41s in the paper of the current implementation of description strategies on a test database of object descriptions.</Paragraph>
  </Section>
class="xml-element"></Paper>