Narrative Analysis of Employment Support for Students With Developmental Disabilities

2022 ◽  
pp. 1827-1843
Author(s):  
Kai Seino ◽  
Yoko Enomoto ◽  
Shiho Miyazawa
Keyword(s):  
Developmental Disabilities ◽  
Text Mining ◽  
Narrative Analysis ◽  
Generation System ◽  
Text Data ◽  
Narrative Generation ◽  
Secondary Result ◽  
Employment Support ◽  
Comprehensive Framework ◽  
Theory Research

The text data regarding the free-expression answers on the employment support provided to students with developmental disabilities (unsure students are included) were defined as the narrative. The aim of this research was to obtain suggestions regarding business solutions that could be used to provide employment support for students with developmental disabilities by conducting text mining and narrative theory analysis. Furthermore, the “narrative generation system” is advocated as a comprehensive framework which organically unifies the whole “narrative phenomenon” from various sides. Furthermore, these researches apply the knowledge of other fields, such as pedagogy on developmental disability, personal support, text mining, and a narratology; psychology; engineering; and literature. Therefore, the authors believe that this research corresponds to “narrative generation system” theory research. Thus, it may be possible for suggestions regarding narrative generation to be produced as a secondary result of this chapter's process of analysis.

Narrative Analysis of Employment Support for Students With Developmental Disabilities

2018 ◽  
pp. 341-357 ◽  
Author(s):  
Kai Seino ◽  
Yoko Enomoto ◽  
Shiho Miyazawa
Keyword(s):  
Developmental Disabilities ◽  
Text Mining ◽  
Narrative Analysis ◽  
Generation System ◽  
Text Data ◽  
Narrative Generation ◽  
Secondary Result ◽  
Employment Support ◽  
Comprehensive Framework ◽  
Theory Research

The text data regarding the free-expression answers on the employment support provided to students with developmental disabilities (unsure students are included) were defined as the narrative. The aim of this research was to obtain suggestions regarding business solutions that could be used to provide employment support for students with developmental disabilities by conducting text mining and narrative theory analysis. Furthermore, the “narrative generation system” is advocated as a comprehensive framework which organically unifies the whole “narrative phenomenon” from various sides. Furthermore, these researches apply the knowledge of other fields, such as pedagogy on developmental disability, personal support, text mining, and a narratology; psychology; engineering; and literature. Therefore, the authors believe that this research corresponds to “narrative generation system” theory research. Thus, it may be possible for suggestions regarding narrative generation to be produced as a secondary result of this chapter's process of analysis.

What Are Narrative Generation Phenomena?

2020 ◽  
pp. 1-58
Keyword(s):  
Artificial Intelligence ◽  
Generation System ◽  
Narrative Generation ◽  
Narrative Structures ◽  
Production And Consumption ◽  
The Future ◽  
Analysis And Synthesis ◽  
Reception System ◽  
Consumption System ◽  
The Individual

First, this chapter introduces an idea that deals with narrative phenomena as the integration between the individual (narrative generation and reception system) and social levels (narrative production and consumption system); this idea is called the “multiple narrative structures model.” This chapter describes the future image of a human-machine symbiosis system that includes narrators and receivers as artificial intelligence. Furthermore, based on the concept of “visible narratives” and “invisible narratives,” the author analyzes the narrative components or elements to consider methods for synthesizing the analyzed elements. This idea of the analysis and synthesis of various narrative elements will be systematized in the “integrated narrative generation system.”

Incorporating Text OLAP in Business Intelligence

2011 ◽  
pp. 77-101 ◽  
Author(s):  
Byung-Kwon Park ◽  
Il-Yeol Song
Keyword(s):  
Information Retrieval ◽  
Text Mining ◽  
Business Intelligence ◽  
Multidimensional Analysis ◽  
Web Pages ◽  
Data Types ◽  
Text Documents ◽  
Text Data ◽  
Platform Architecture ◽  
Unstructured Text

As the amount of data grows very fast inside and outside of an enterprise, it is getting important to seamlessly analyze both data types for total business intelligence. The data can be classified into two categories: structured and unstructured. For getting total business intelligence, it is important to seamlessly analyze both of them. Especially, as most of business data are unstructured text documents, including the Web pages in Internet, we need a Text OLAP solution to perform multidimensional analysis of text documents in the same way as structured relational data. We first survey the representative works selected for demonstrating how the technologies of text mining and information retrieval can be applied for multidimensional analysis of text documents, because they are major technologies handling text data. And then, we survey the representative works selected for demonstrating how we can associate and consolidate both unstructured text documents and structured relation data for obtaining total business intelligence. Finally, we present a future business intelligence platform architecture as well as related research topics. We expect the proposed total heterogeneous business intelligence architecture, which integrates information retrieval, text mining, and information extraction technologies all together, including relational OLAP technologies, would make a better platform toward total business intelligence.

Designing a Socially Open Narrative Generation System

2016 ◽  
pp. 91-117 ◽  
Author(s):  
Taisuke Akimoto ◽  
Takashi Ogata
Keyword(s):  
Computer Program ◽  
Mechanism Design ◽  
Social Process ◽  
Social Activity ◽  
Computational Approach ◽  
Generation System ◽  
Narrative Generation ◽  
The Social ◽  
Key Concepts ◽  
Generation Technology

The authors propose the design of a Socially Open Narrative Generation System (SONGS) that co-creates a collection of diverse narratives from a narrative generation program and people. This is a challenge of the social application of narrative generation technology used for vitalizing the social activity of producing and sharing narratives. The key idea is to connect and unify individual narrative productions by many agents, including a computer program and many humans, via a collection of narratives produced and accumulated by these agents. At the same time, SONGS is the practice of a computational approach to narratology as a model for the social process of narrative production. This chapter describes the key concepts and mechanism design of SONGS with several experimental programs.

The Expansion of Paths in the Mutual Transformation Mechanism of Music and Narrative

2013 ◽  
Vol 7 (4) ◽  
pp. 44-63 ◽  
Author(s):  
Taisuke Akimoto ◽  
Jun Endo ◽  
Takashi Ogata
Keyword(s):  
System Architecture ◽  
Conceptual Knowledge ◽  
Surface Expression ◽  
Mutual Transformation ◽  
Generation System ◽  
Transformation Mechanism ◽  
Narrative Generation ◽  
Musical Knowledge ◽  
Automatic Composition

For a mechanism of the surface expression phase in the authors' narrative generation system architecture, this paper proposes an approach to the circulative generation by the mutual transformation between music and narrative. In the concept for musical mechanism, music is not just the accompaniment for narrative and the authors extremely aim at using musical knowledge & techniques and conceptual knowledge & techniques in fusion by the medium of music. Depending on this concept, in this paper, the authosr introduce the newest prototyping system composed of eight routes of transformation modules between narrative and music including automatic composition and musical variation mechanisms. In addition, through the simple preliminary evaluations, the authors consider several insufficient points in the quality of music and the correspondence of music to narrative.

Text Mining to Support Consulting Services for Client Company State Recognition

2020 ◽  
Vol 14 (5) ◽  
pp. 779-790
Author(s):  
Ruriko Watanabe ◽  
Nobutada Fujii ◽  
Daisuke Kokuryo ◽  
Toshiya Kaihara ◽  
Yoichi Abe ◽  
...  
Keyword(s):  
Text Mining ◽  
Support System ◽  
Computer Experiments ◽  
Text Data ◽  
Logistic Regression Models ◽  
Service Companies ◽  
Consulting Services ◽  
Customer Information ◽  
Problem Detection ◽  
Specialized Service

This study was conducted to devise a method for supporting consulting service companies in their response to client demands irrespective of the expertise of consultants. With emphasis on revitalization of small and medium-sized enterprises, the importance of support systems for consulting services to serve them is increasing. Those systems must support solutions to difficulties that must be addressed by enterprises. Consulting companies can respond to widely various management consultations. Nevertheless, because the consultation contents are highly specialized, service proposals and problem detection depend on the experience and intuition of the consultant. Often, stable service cannot be provided. A support system must provide stable services independent of the ability of consultants. In this study, analyzing customer information describing the contents of consultation with client companies is the first step in constructing a support system that can predict future problems. Text data such as a consultant’s visit history, consultation contents by e-mail, and contents of call centers are used for analyses because the contents can explain current problems. They might also indicate future problems. This report describes a method to analyze text data using text mining. The target problem is fraud, which includes uncertainty: cases in which it is not clear whether a fraud problem has occurred with the company. To address uncertainty, a method of using logistic regression models is proposed to represent inferred values as probabilities, rather than as binary discriminated data, because the possibility exists that some misidentified companies might have some difficulty. As described herein, computer experiments are conducted to verify the effectiveness of the proposed method and to compare consultants’ forecasted and achieved results. Results of a verification experiment are presented in the following. First, the proposed method is applicable to problems including uncertainties. Secondly, the possibility exists of discovering companies with a fraud problem of which they are unaware.

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