A linguistics-based approach to refining automatic intent detection in conversational agent design

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3A4Z6CTRHD" target="_blank" >RIV/00216208:11320/26:4Z6CTRHD - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204348144&doi=10.1016%2fj.ins.2024.121493&partnerID=40&md5=220b426249cb41bdf3eeeb76441a3e72" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204348144&doi=10.1016%2fj.ins.2024.121493&partnerID=40&md5=220b426249cb41bdf3eeeb76441a3e72</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ins.2024.121493" target="_blank" >10.1016/j.ins.2024.121493</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A linguistics-based approach to refining automatic intent detection in conversational agent design

Popis výsledku v původním jazyce

In this paper, we propose Automatic Intent Detector (AID), a framework for automatic intent detection to facilitate the creation of a conversational agent. AID follows an eight-step process incorporating best practices from the current literature and introducing innovative approaches in certain steps. The most notable innovation within AID is the automatic labeling of clusters, which is based on detailed and sophisticated rules derived from linguistics. These rules focus on morphosyntactic analysis, while also taking into account an aspect of semantic role theory. Furthermore, as for the overall validation of the results obtained, it provides an approach based on the concepts of semantic coherence, variability, and label appropriateness. After describing AID at the technical level, we illustrate the experiments we conducted both on a dataset widely used as benchmark in the literature and on a real corporate dataset. Finally, we present a critical discussion on the results obtained. © 2024 The Author(s)

Název v anglickém jazyce

A linguistics-based approach to refining automatic intent detection in conversational agent design

Popis výsledku anglicky

In this paper, we propose Automatic Intent Detector (AID), a framework for automatic intent detection to facilitate the creation of a conversational agent. AID follows an eight-step process incorporating best practices from the current literature and introducing innovative approaches in certain steps. The most notable innovation within AID is the automatic labeling of clusters, which is based on detailed and sophisticated rules derived from linguistics. These rules focus on morphosyntactic analysis, while also taking into account an aspect of semantic role theory. Furthermore, as for the overall validation of the results obtained, it provides an approach based on the concepts of semantic coherence, variability, and label appropriateness. After describing AID at the technical level, we illustrate the experiments we conducted both on a dataset widely used as benchmark in the literature and on a real corporate dataset. Finally, we present a critical discussion on the results obtained. © 2024 The Author(s)

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Information Sciences

ISSN

0020-0255

e-ISSN

—

Svazek periodika

689

Číslo periodika v rámci svazku

2025

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

22

Strana od-do

1-22

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85204348144