<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="galitsky-etal-2020-chatbot">
    <titleInfo>
        <title>On a Chatbot Navigating a User through a Concept-Based Knowledge Model</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Boris</namePart>
        <namePart type="family">Galitsky</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Dmitry</namePart>
        <namePart type="family">Ilvovsky</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Elizaveta</namePart>
        <namePart type="family">Goncharova</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2020-12</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of Workshop on Natural Language Processing in E-Commerce</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Huasha</namePart>
            <namePart type="family">Zhao</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Parikshit</namePart>
            <namePart type="family">Sondhi</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Nguyen</namePart>
            <namePart type="family">Bach</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Sanjika</namePart>
            <namePart type="family">Hewavitharana</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Yifan</namePart>
            <namePart type="family">He</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Luo</namePart>
            <namePart type="family">Si</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Heng</namePart>
            <namePart type="family">Ji</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Barcelona, Spain</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Information retrieval chatbots are widely used as assistants, to help users formulate their requirements about the products they want to purchase, and navigate to the set of items that satisfies their requirements in the best way. The work of the modern chatbots is based mostly on the deep learning theory behind the knowledge model that can improve the performance of the system. In our work, we are developing a concept-based knowledge model that encapsulates objects and their common descriptions. The leveraging of the concept-based knowledge model allows the system to refine the initial users’ requests and lead them to the set of objects with the maximal variability of parameters that matters less to them. Introducing the additional textual characteristics allows users to formulate their initial query as a phrase in natural language, rather than as some standard request in the form of, “Attribute - value”.</abstract>
    <identifier type="citekey">galitsky-etal-2020-chatbot</identifier>
    <location>
        <url>https://aclanthology.org/2020.ecomnlp-1.6</url>
    </location>
    <part>
        <date>2020-12</date>
        <extent unit="page">
            <start>53</start>
            <end>65</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T On a Chatbot Navigating a User through a Concept-Based Knowledge Model
%A Galitsky, Boris
%A Ilvovsky, Dmitry
%A Goncharova, Elizaveta
%Y Zhao, Huasha
%Y Sondhi, Parikshit
%Y Bach, Nguyen
%Y Hewavitharana, Sanjika
%Y He, Yifan
%Y Si, Luo
%Y Ji, Heng
%S Proceedings of Workshop on Natural Language Processing in E-Commerce
%D 2020
%8 December
%I Association for Computational Linguistics
%C Barcelona, Spain
%F galitsky-etal-2020-chatbot
%X Information retrieval chatbots are widely used as assistants, to help users formulate their requirements about the products they want to purchase, and navigate to the set of items that satisfies their requirements in the best way. The work of the modern chatbots is based mostly on the deep learning theory behind the knowledge model that can improve the performance of the system. In our work, we are developing a concept-based knowledge model that encapsulates objects and their common descriptions. The leveraging of the concept-based knowledge model allows the system to refine the initial users’ requests and lead them to the set of objects with the maximal variability of parameters that matters less to them. Introducing the additional textual characteristics allows users to formulate their initial query as a phrase in natural language, rather than as some standard request in the form of, “Attribute - value”.
%U https://aclanthology.org/2020.ecomnlp-1.6
%P 53-65

Markdown (Informal)

[On a Chatbot Navigating a User through a Concept-Based Knowledge Model](https://aclanthology.org/2020.ecomnlp-1.6) (Galitsky et al., EcomNLP 2020)

• On a Chatbot Navigating a User through a Concept-Based Knowledge Model (Galitsky et al., EcomNLP 2020)

ACL

• Boris Galitsky, Dmitry Ilvovsky, and Elizaveta Goncharova. 2020. On a Chatbot Navigating a User through a Concept-Based Knowledge Model. In Proceedings of Workshop on Natural Language Processing in E-Commerce, pages 53–65, Barcelona, Spain. Association for Computational Linguistics.