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<Paper uid="C94-2197">
  <Title>A Bayesian Approach for User Modeling in Dialogue Systems</Title>
  <Section position="7" start_page="7272" end_page="7272" type="concl">
    <SectionTitle>
5 Conclusion
</SectionTitle>
    <Paragraph position="0"> We, have prol)osed the \]:htyesian approadt for user modeling in dialogue syst;ems. The knowledge rcpresenl:at.ion, in l;e, rms o\[ \]\]~wesian net:works, figs been tlist:uss(;d. Rcasoniltg would I)c aatl;mnatit:;dly ~uld (lirecl;ly t)erformed l)y ewtlu;d, ing tim network followed by sl:oeh~Lsl;ic simulation.</Paragraph>
    <Paragraph position="1"> Most exact, solutions for |;he inl:eresting problents in a.rt;ilicial intelligmlce are knowtl 1.o have NP-hard comput~d.i(ma\] complexil:y. '12hus, it luts beelL l'ecognized tfia.t solving t.hem by ;tic al)t)roximal.e method is a more realistic a.pproach. ~Phe \]\];tyesi~ul nel;works ;~rc (wMmd;cd l)y the stocha, si;ic sinmhd:iol h which is the ai)l)rOXilll~tt(: solut.iol, of probM)ilist;ic reasm,ing. The simuhd:iml cost, however, is still expellsive with the present COmlml:ing resources. The imr~dlel imphmmnl;;tlion has relmrl;ed good performance resull:s \[7\]. After gaining l;hc' aecur;d;e expeetalions of user models, a mechamism to ll.q(: t;helll for utterance genet'~tl;ion is required. This will be done by planners for uLt;erance /';e,eration, whM, try to ~chieve the system's goals, The In'ol~al*ilil;ie, s in the user model conla'ibute to measure 1:o wh;tt exl, cnt the pl~ul will succeed.</Paragraph>
    <Paragraph position="2"> In the study of nat;urM lauguage processing, Bayesian ;tl~proatt:hes lmve bee, ;Ldolfl:ed in t.he field of t,hm recoglfidon \[3\] and lexical dis;unbiguation \[7\].</Paragraph>
    <Paragraph position="3"> We have adopted tile \]l~tyesi;ul networks for user Inodcling because we have pereeiw',d that user modeling is one of the core components of diMogue systems whose 1)eh~wim&amp;quot; strongly iMluences t;he otl,e,' parts of the sys\[;elll. We ende~tvor I;o eclnsl;rllct |;fie eXl)erilllellt~tl diglogue syslmln I;hat accepts l;he users' inputs by speech recognit;ion\[8\]. Sl;;trting with user modeling, we' will ex- null i)and th(; adoption of Bayesian al)l)roaches in most of the eomi)onents in the system. The al)l)roaches must be quite effective ill the other colni)onellts , and lead to a systeIn whose contl)onents closely interact with each other on the common basis of t)i'obability theory.</Paragraph>
  </Section>
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