A Rule-Based Approach for Model Management in a User Interface – Business Alignment Framework

2010 ◽  
pp. 1-14 ◽  
Author(s):  
Kenia Sousa ◽  
Hildeberto Mendonça ◽  
Jean Vanderdonckt
Keyword(s):  
User Interface ◽  
Model Management ◽  
Rule Based ◽  
Business Alignment ◽  
Rule Based Approach

Self-Anamnesis with a Conversational User Interface: Concept and Usability Study

2018 ◽  
Vol 57 (05/06) ◽  
pp. 243-252 ◽  
Author(s):  
Sandra Hochreutener ◽  
Annkathrin Pöpel ◽  
Richard May ◽  
Kerstin Denecke
Keyword(s):  
User Interface ◽  
Health Care Team ◽  
Markup Language ◽  
Usability Study ◽  
Medical Assistant ◽  
Current Version ◽  
Music Therapists ◽  
Rule Based ◽  
Rule Based Approach

Objective Self-anamnesis is a procedure in which a patient answers questions about the personal medical history without interacting directly with a doctor or medical assistant. If collected digitally, the anamnesis data can be shared among the health care team. In this article, we introduce a concept for digital anamnesis collection and assess the applicability of a conversational user interface (CUI) for realizing a mobile self-anamnesis application. Materials and Methods We implemented our concept for self-anamnesis for the concrete field of music therapy. We collected requirements with respect to the application from music therapists and by reviewing the literature. A rule-based approach was chosen for realizing the anamnesis conversation between the system and the user. The Artificial Intelligence Markup Language was exploited for encapsulating the questions and responses of the system. For studying the quality of the system and analyzing performance, humanity, effect, and accessibility of the system, we performed a usability test with 22 persons. Results The current version of the self-anamnesis application is equipped with 63 questions on the music biography of a patient that are asked subsequently to the user by means of a chatbot conversation. The usability study showed that a CUI is a practical way for collecting anamnesis data. Users felt engaged of answering the questions and liked the human characteristics of the chatbot. They suggested to extend the conversation capabilities of the chatbot so that the system can react appropriately, in particular when the user is not feeling well. Conclusions We could demonstrate the applicability of a CUI for collecting anamnesis data. In contrast to digital anamnesis questionnaires, the application of a CUI provides several benefits: the user can be encouraged to complete all queries and can ask clarifying questions in case something is unclear.

A Brief Survey on Text Classification Using Various Machine Learning Techniques

2018 ◽  
Vol 8 (1) ◽  
pp. 14
Author(s):  
Padmavathi .S ◽  
M. Chidambaram
Keyword(s):  
Machine Learning ◽  
Text Classification ◽  
Fixed Number ◽  
Machine Learning Techniques ◽  
Online Information ◽  
Rule Based ◽  
Learning Techniques ◽  
Machine Learning Approach ◽  
Rule Based Approach

Text classification has grown into more significant in managing and organizing the text data due to tremendous growth of online information. It does classification of documents in to fixed number of predefined categories. Rule based approach and Machine learning approach are the two ways of text classification. In rule based approach, classification of documents is done based on manually defined rules. In Machine learning based approach, classification rules or classifier are defined automatically using example documents. It has higher recall and quick process. This paper shows an investigation on text classification utilizing different machine learning techniques.

MRI Brain Tumor Image Analysis Using Fuzzy Rule based Approach

2019 ◽  
Vol 50 (2) ◽  
pp. 98-112 ◽  
Author(s):  
KALYAN KUMAR JENA ◽  
SASMITA MISHRA ◽  
SAROJANANDA MISHRA ◽  
SOURAV KUMAR BHOI ◽  
SOUMYA RANJAN NAYAK
Keyword(s):  
Image Analysis ◽  
Brain Tumor ◽  
Fuzzy Rule ◽  
Rule Based ◽  
Mri Brain ◽  
Rule Based Approach

Rule-based Approach to Semantic Resolution of Chinese Addresses

2010 ◽  
Vol 12 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Xueying ZHNAG ◽  
Guonian LV ◽  
Boqiu LI ◽  
Wenjun CHEN
Keyword(s):  
Rule Based ◽  
Semantic Resolution ◽  
Rule Based Approach

An Automatic Question Generation System using Rule-Based Approach in Bloom’s Taxonomy

2019 ◽  
Vol 13 ◽  
Author(s):  
G Deena ◽  
K Raja ◽  
K Kannan
Keyword(s):  
Language Processing ◽  
Learning Process ◽  
Question Generation ◽  
Test Question ◽  
Rule Based ◽  
Part Of Speech ◽  
Core Idea ◽  
Rule Based Approach ◽  
Teaching Learning ◽  
Automatic Question Generation

: In this competing world, education has become part of everyday life. The process of imparting the knowledge to the learner through education is the core idea in the Teaching-Learning Process (TLP). An assessment is one way to identify the learner’s weak spot of the area under discussion. An assessment question has higher preferences in judging the learner's skill. In manual preparation, the questions are not assured in excellence and fairness to assess the learner’s cognitive skill. Question generation is the most important part of the teaching-learning process. It is clearly understood that generating the test question is the toughest part. Methods: Proposed an Automatic Question Generation (AQG) system which automatically generates the assessment questions dynamically from the input file. Objective: The Proposed system is to generate the test questions that are mapped with blooms taxonomy to determine the learner’s cognitive level. The cloze type questions are generated using the tag part-of-speech and random function. Rule-based approaches and Natural Language Processing (NLP) techniques are implemented to generate the procedural question of the lowest blooms cognitive levels. Analysis: The outputs are dynamic in nature to create a different set of questions at each execution. Here, input paragraph is selected from computer science domain and their output efficiency are measured using the precision and recall.

Rule‐Based Approach for Botnet Behavior Analysis

2021 ◽  
pp. 161-179
Author(s):  
Supriya Raheja ◽  
Geetika Munjal ◽  
Jyoti Jangra ◽  
Rakesh Garg
Keyword(s):  
Behavior Analysis ◽  
Rule Based ◽  
Rule Based Approach
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