Knowledge Graphs and Representational Models for Dialogue Systems

Nicholas Thomas Walker

Knowledge Graphs and Representational Models for Dialogue Systems

Correct Metadata for

Important: The Anthology treat PDFs as authoritative. Please use this form only to correct data that is out of line with the PDF. See our corrections guidelines if you need to change the PDF.

Title Adjust the title. Retain tags such as <fixed-case>.

Authors Adjust author names and order to match the PDF.

Abstract Correct abstract if needed. Retain XML formatting tags such as <tex-math>.

Verification against PDF Ensure that the new title/authors match the snapshot below. (If there is no snapshot or it is too small, consult the PDF.)

Authors concatenated from the text boxes above:

ALL author names match the snapshot above—including middle initials, hyphens, and accents.

Abstract

I am interested graph-based dialogue management for dialogue systems, specifically the use of knowledge- graphs. Representations of knowledge combining in- formation about the world with dialogue or user-specific information, such as personal knowledge graphs (Balog and Kenter, 2019) are of particular interest to me. Knowl- edge graphs have the flexibility to represent diverse in- formation such as dialogue specific information, gen- eral world knowledge, and even situated knowledge in the case of embodied dialogue systems. Much of my previous work has investigated knowledge graphs in an HRI context that combined these attributes (Walker et al., 2022b).

Anthology ID:: 2025.yrrsds-1.9
Volume:: Proceedings of the 21st Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems
Month:: August
Year:: 2025
Address:: Avignon, France
Editors:: Ryan Whetten, Virgile Sucal, Anh Ngo, Kranti Chalamalasetti, Koji Inoue, Gaetano Cimino, Zachary Yang, Yuki Zenimoto, Ricardo Rodriguez
Venue:: YRRSDS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 25–26
Language:
URL:: https://aclanthology.org/2025.yrrsds-1.9/
DOI:
Bibkey:
Cite (ACL):: Nicholas Thomas Walker. 2025. Knowledge Graphs and Representational Models for Dialogue Systems. In Proceedings of the 21st Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems, pages 25–26, Avignon, France. Association for Computational Linguistics.
Cite (Informal):: Knowledge Graphs and Representational Models for Dialogue Systems (Walker, YRRSDS 2025)
Copy Citation:
PDF:: https://aclanthology.org/2025.yrrsds-1.9.pdf

PDF Cite Search Fix data

Export citation

BibTeX
MODS XML
Endnote
Preformatted

@inproceedings{walker-2025-knowledge,
    title = "Knowledge Graphs and Representational Models for Dialogue Systems",
    author = "Walker, Nicholas Thomas",
    editor = "Whetten, Ryan  and
      Sucal, Virgile  and
      Ngo, Anh  and
      Chalamalasetti, Kranti  and
      Inoue, Koji  and
      Cimino, Gaetano  and
      Yang, Zachary  and
      Zenimoto, Yuki  and
      Rodriguez, Ricardo",
    booktitle = "Proceedings of the 21st Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems",
    month = aug,
    year = "2025",
    address = "Avignon, France",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.yrrsds-1.9/",
    pages = "25--26",
    abstract = "I am interested graph-based dialogue management for dialogue systems, specifically the use of knowledge- graphs. Representations of knowledge combining in- formation about the world with dialogue or user-specific information, such as personal knowledge graphs (Balog and Kenter, 2019) are of particular interest to me. Knowl- edge graphs have the flexibility to represent diverse in- formation such as dialogue specific information, gen- eral world knowledge, and even situated knowledge in the case of embodied dialogue systems. Much of my previous work has investigated knowledge graphs in an HRI context that combined these attributes (Walker et al., 2022b)."
}

Download as File

<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="walker-2025-knowledge">
    <titleInfo>
        <title>Knowledge Graphs and Representational Models for Dialogue Systems</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Nicholas</namePart>
        <namePart type="given">Thomas</namePart>
        <namePart type="family">Walker</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2025-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 21st Workshop of Young Researchers’ Roundtable on Spoken Dialogue Systems</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Ryan</namePart>
            <namePart type="family">Whetten</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Virgile</namePart>
            <namePart type="family">Sucal</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Anh</namePart>
            <namePart type="family">Ngo</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Kranti</namePart>
            <namePart type="family">Chalamalasetti</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Koji</namePart>
            <namePart type="family">Inoue</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Gaetano</namePart>
            <namePart type="family">Cimino</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Zachary</namePart>
            <namePart type="family">Yang</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Yuki</namePart>
            <namePart type="family">Zenimoto</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Ricardo</namePart>
            <namePart type="family">Rodriguez</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Avignon, France</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>I am interested graph-based dialogue management for dialogue systems, specifically the use of knowledge- graphs. Representations of knowledge combining in- formation about the world with dialogue or user-specific information, such as personal knowledge graphs (Balog and Kenter, 2019) are of particular interest to me. Knowl- edge graphs have the flexibility to represent diverse in- formation such as dialogue specific information, gen- eral world knowledge, and even situated knowledge in the case of embodied dialogue systems. Much of my previous work has investigated knowledge graphs in an HRI context that combined these attributes (Walker et al., 2022b).</abstract>
    <identifier type="citekey">walker-2025-knowledge</identifier>
    <location>
        <url>https://aclanthology.org/2025.yrrsds-1.9/</url>
    </location>
    <part>
        <date>2025-08</date>
        <extent unit="page">
            <start>25</start>
            <end>26</end>
        </extent>
    </part>
</mods>
</modsCollection>

Download as File

%0 Conference Proceedings
%T Knowledge Graphs and Representational Models for Dialogue Systems
%A Walker, Nicholas Thomas
%Y Whetten, Ryan
%Y Sucal, Virgile
%Y Ngo, Anh
%Y Chalamalasetti, Kranti
%Y Inoue, Koji
%Y Cimino, Gaetano
%Y Yang, Zachary
%Y Zenimoto, Yuki
%Y Rodriguez, Ricardo
%S Proceedings of the 21st Workshop of Young Researchers’ Roundtable on Spoken Dialogue Systems
%D 2025
%8 August
%I Association for Computational Linguistics
%C Avignon, France
%F walker-2025-knowledge
%X I am interested graph-based dialogue management for dialogue systems, specifically the use of knowledge- graphs. Representations of knowledge combining in- formation about the world with dialogue or user-specific information, such as personal knowledge graphs (Balog and Kenter, 2019) are of particular interest to me. Knowl- edge graphs have the flexibility to represent diverse in- formation such as dialogue specific information, gen- eral world knowledge, and even situated knowledge in the case of embodied dialogue systems. Much of my previous work has investigated knowledge graphs in an HRI context that combined these attributes (Walker et al., 2022b).
%U https://aclanthology.org/2025.yrrsds-1.9/
%P 25-26

Download as File

Markdown (Informal)

[Knowledge Graphs and Representational Models for Dialogue Systems](https://aclanthology.org/2025.yrrsds-1.9/) (Walker, YRRSDS 2025)

Knowledge Graphs and Representational Models for Dialogue Systems (Walker, YRRSDS 2025)

ACL

Nicholas Thomas Walker. 2025. Knowledge Graphs and Representational Models for Dialogue Systems. In Proceedings of the 21st Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems, pages 25–26, Avignon, France. Association for Computational Linguistics.