---
_id: '29000'
abstract:
- lang: eng
text: "This thesis aims to provide a bidirectional chatbot solution for the requirement
engineering process. The Sonderforschungsbereich (SFB) 901 intends to provide
the composition of software service On-the-Fly (OTF). The sub-project (B1) of
the SFB 901 project deals with the parameters of service configuration. OTF Computing
aims to eradicate the dependency on the requirement engineers for the software
development process. However, there is no existing bidirectional chatbot solution
that analyses user software requirements and provides viable suggestions to the
user regarding their service. Previously, CORDULA chatbot was developed to analyze
the software requirements but cannot keep the conversation’s context. The Rasa
framework is integrated with the knowledge base to solve the issue, the knowledge
base provides domain-specific knowledge to the chatbot. The software description
is passed through the natural language understanding process to give consciousness
to the chatbot. This process involves various machine learning models, including
app family classification, to correctly identify the domain for user OTF service.
The statistical models like naïve Bayes, kNN and SVM are compared with transformer
models for this classification task. Furthermore, the entities (functional requirements)
are also separated from the user description.\r\nThe chatbot provides the suggestion
of requirements from the preliminary service template with the support of the
knowledge base. Furthermore, the generated response is compared with the state-of-the-art
DialoGPT transformer model and ChatterBot conversational library. These models
are trained over the software development related conversational dataset. All
the responses are ranked using the DialoRPT model, and the BLEU score to evaluates
the models’ responses. Moreover, the chatbot mod- els are tested with human participants,
they used and scored the chatbot responses based on effectiveness, efficiency
and satisfaction. The overall response accuracy is also measured by averaging
the user approval over the generated responses."
author:
- first_name: Mobeen
full_name: Ahmed, Mobeen
last_name: Ahmed
citation:
ama: Ahmed M. Knowledge Base Enhanced & User-Centric Dialogue Design for
OTF Computing.; 2022.
apa: Ahmed, M. (2022). Knowledge Base Enhanced & User-centric Dialogue Design
for OTF Computing.
bibtex: '@book{Ahmed_2022, title={Knowledge Base Enhanced & User-centric Dialogue
Design for OTF Computing}, author={Ahmed, Mobeen}, year={2022} }'
chicago: Ahmed, Mobeen. Knowledge Base Enhanced & User-Centric Dialogue Design
for OTF Computing, 2022.
ieee: M. Ahmed, Knowledge Base Enhanced & User-centric Dialogue Design for
OTF Computing. 2022.
mla: Ahmed, Mobeen. Knowledge Base Enhanced & User-Centric Dialogue Design
for OTF Computing. 2022.
short: M. Ahmed, Knowledge Base Enhanced & User-Centric Dialogue Design for
OTF Computing, 2022.
date_created: 2021-12-16T15:13:07Z
date_updated: 2023-05-02T13:25:45Z
ddc:
- '004'
department:
- _id: '600'
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2023-05-02T13:25:27Z
date_updated: 2023-05-02T13:25:27Z
file_id: '44325'
file_name: Thesis-Report-MOBEEN-AHMED-6856465-Knowledge_Base_Enhanced___User_centric_Dialogue_Design_for_OTFComputing.pdf
file_size: 3092211
relation: main_file
success: 1
file_date_updated: 2023-05-02T13:25:27Z
has_accepted_license: '1'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
publication_status: published
status: public
supervisor:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
title: Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing
type: mastersthesis
user_id: '58701'
year: '2022'
...