A multi-level conceptual data reduction approach based on the Lukasiewicz implication

A challenging area of pattern recognition is the recognition of handwritten texts in different languages and the reduction of a volume of data to the greatest extent while preserving associations (or dependencies) between objects of the original data. Until now, only a few studies have been carried out in the area of dimensionality reduction for handedness detection from off-line handwriting textual data. Nevertheless, further investigating new techniques to reduce the large amount of processed data in this field is worthwhile. In this paper, we demonstrate that it is important to select only the most characterizing features from handwritings and reject all those that do not contribute effectively to the process of handwriting recognition. To achieve this goal, the proposed approach is based mainly on fuzzy conceptual reduction by applying the Lukasiewicz implication. Handwritten texts in both Arabic and English languages are considered in this study. To evaluate the effectiveness of our proposal approach, classification is carried out using a K-Nearest-Neighbors (K-NN) classifier using a database of 121 writers. We consider left/right handedness as parameters for the evaluation where we determine the recall/precision and F-measure of each writer. Then, we apply dimensionality reduction based on fuzzy conceptual reduction by using the Lukasiewicz implication. Our novel feature reduction method achieves a maximum reduction rate of 83.43 %, thus making the testing phase much faster. The proposed fuzzy conceptual reduction algorithm is able to reduce the feature vector dimension by 31.3 % compared to the original "BEST OF ALL COMBINED FEATURES" algorithm.

show abstract

“…Formal Concept Analysis (FCA) is the mathematical theory of data analysis using formal contexts and concept lattices [12][13][14] [16,17].…”

Section: Formal Concept Analysismentioning

confidence: 99%

A novel approach for handedness detection from off-line handwriting using fuzzy conceptual reduction

Al-Maadeed

Ferjani

Elloumi

et al. 2016

J Image Video Proc.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Jaam et al [8,9] have developed new algorithms for Arabic text summarization, and automatic data classification. Elloumi et al [10] developed data reduction and redundancy elimination algorithms, and knowledge extraction from Arabic and English news [11]. While technologies have been developed attempting to tackle the semantic analysis of digital content, there exists no global approach or solution to the low-level analysis of Arabic media.…”

Section: Introductionmentioning

confidence: 99%

Audio-Textual Classification System Design for Arabic News Videos

Dandashi¹,

Ja’am²,

Foufou³

2016

IJCIS

View full text Add to dashboard Cite

“…With their lattice structures and attribute implications, concept lattices support KDD. The crucial issue towards the discovery of knowledge using FCA is knowledge reduction while maintaining structure consistency (Aswani Kumar and Srinivas, 2010a;Belohlavek and Vychodil, 2010;Elloumi et al, 2004, Wu et al, 2009. Hence the goal is to minimize the input data before applying FCA.…”

Section: Introductionmentioning

confidence: 99%

Knowledge discovery in data using formal concept analysis and random projections

Cherukuri¹

2011

International Journal of Applied Mathematics and Computer Science

View full text Add to dashboard Cite

In this paper our objective is to propose a random projections based formal concept analysis for knowledge discovery in data. We demonstrate the implementation of the proposed method on two real world healthcare datasets. Formal Concept Analysis (FCA) is a mathematical framework that offers a conceptual knowledge representation through hierarchical conceptual structures called concept lattices. However, during the design of a concept lattice, complexity plays a major role.

show abstract

A multi-level conceptual data reduction approach based on the Lukasiewicz implication

Cited by 91 publications

References 7 publications

A novel approach for handedness detection from off-line handwriting using fuzzy conceptual reduction

A novel approach for handedness detection from off-line handwriting using fuzzy conceptual reduction

Audio-Textual Classification System Design for Arabic News Videos

Knowledge discovery in data using formal concept analysis and random projections

Contact Info

Product

Resources

About