Rule-based Approach for Context Inconsistency Management Scheme in Ubiquitous Computing

2010 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing ◽

10.1109/euc.2010.27 ◽

2010 ◽

Cited By ~ 1

Author(s):

Yong-jae Lee ◽

Jaehyoung Lim ◽

Soon J. Hyun ◽

Dongman Lee

Keyword(s):

Ubiquitous Computing ◽

Rule Based ◽

Management Scheme ◽

Inconsistency Management ◽

Rule Based Approach

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A Brief Survey on Text Classification Using Various Machine Learning Techniques

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v8i1.521 ◽

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.

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MRI Brain Tumor Image Analysis Using Fuzzy Rule based Approach

Journal of Research on the Lepidoptera ◽

10.36872/lepi/v50i2/201012 ◽

2019 ◽

Vol 50 (2) ◽

pp. 98-112 ◽

Cited By ~ 5

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

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Rule-based Approach to Semantic Resolution of Chinese Addresses

Geo-information Science ◽

10.3724/sp.j.1047.2010.00009 ◽

2010 ◽

Vol 12 (1) ◽

pp. 9-16 ◽

Cited By ~ 3

Author(s):

Xueying ZHNAG ◽

Guonian LV ◽

Boqiu LI ◽

Wenjun CHEN

Keyword(s):

Rule Based ◽

Semantic Resolution ◽

Rule Based Approach

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

Recent Advances in Computer Science and Communications ◽

10.2174/2213275912666191113143335 ◽

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.

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