학술논문

Context Classification in Dialog-Based Interaction
Document Type
Conference
Source
2020 IEEE 14th International Conference on Semantic Computing (ICSC) Semantic Computing (ICSC, 2020 IEEE 14th International Conference on. :185-189 Feb, 2020
Subject
Computing and Processing
Natural languages
Syntactics
History
Semantics
Programming
Software
Unified modeling language
Context
Natural Language User Interfaces
Human Computer Interaction
Classification
Language
Abstract
A difficulty in processing of the natural language is recognizing the context of a statement. However, since this contains implicit knowledge which we unconsciously use in our formulations, it is necessary to assign the context for correct interpretation. A context in our system is managed by a service that interprets and processes input and provides feedback to the end user. In this paper, we present a solution how an end user input can be assigned to such a service. For this purpose, we score the end user inputs by the system with an ensemble of 6 different classifiers that consider semantics as well as syntax. The system learns the user's input at run time and adapts his enunciation step by step. During the evaluation, the system was able to classified 87% of the user statements to the correct service. Far from perfect, this research might lead to fundamental changes in computer use.