Models for Narrative Information: A Study

TL;DR

This paper systematically reviews and compares ontology-driven models for narrative information across various domains, highlighting their similarities, differences, and the current state of research in this area.

Contribution

It provides a comprehensive comparative analysis of existing ontology-based narrative models and evaluates them using narrative components, unifying literature under one framework.

Findings

Identified key similarities and differences in knowledge representation across domains.

Highlighted the scarcity of reviews on ontology-based narrative models.

Evaluated ontologies using parameters derived from narrative components.

Abstract

The major objective of this work is to study and report the existing ontology-driven models for narrative information. The paper aims to analyze these models across various domains. The goal of this work is to bring the relevant literature, and ontology models under one umbrella, and perform a parametric comparative study. A systematic literature review methodology was adopted for an extensive literature selection. A random stratified sampling technique was used to select the models from the literature. The findings explicate a comparative view of the narrative models across domains. The differences and similarities of knowledge representation across domains, in case of narrative information models based on ontology was identified. There are significantly fewer studies that reviewed the ontology-based narrative models. This work goes a step further by evaluating the ontologies using the parameters from narrative components. This paper will explore the basic concepts and top-level concepts in the models. Besides, this study provides a comprehensive study of the narrative theories in the context of ongoing research. The findings of this work demonstrate the similarities and differences among the elements of the ontology across domains. It also identifies the state of the art literature for ontology-based narrative information.