Optimized weights of document keywords for auto-reply accuracy

A Taguchi-crossover differential evolution (TCDE) algorithm is proposed to optimize weights of document keywords for auto-reply accuracy. The proposed TCDE algorithm combines the use of differential evolution for exploring the optimal feasible region in macro-space with the use of the Taguchi method...

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Veröffentlicht in:Neurocomputing (Amsterdam) Jg. 124; S. 43 - 56
1. Verfasser: Tsai, Jinn-Tsong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 26.01.2014
Elsevier
Schlagworte:
Algorithmics. Computability. Computer arithmetics
Algorithms
Applied sciences
Auto-reply accuracy
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Data processing. List processing. Character string processing
Differential evolution
e-learning
Evolutionary algorithms
Exact sciences and technology
General aspects
Keyword weight
Learning
Memory organisation. Data processing
Occupational training. Personnel. Work management
Optimization
Query processing
Similarity
Software
Students
Taguchi method
Teachers
Theoretical computing
Differential evolution
e-learning
Auto-reply accuracy
Keyword weight
Taguchi method
Keyword
Similarity
Evolutionary algorithm
Remote teaching
Teaching
Function evaluation
Experimental design
Optimal solution
Metric
Internet
ISSN:0925-2312, 1872-8286
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Beschreibung
Zusammenfassung:A Taguchi-crossover differential evolution (TCDE) algorithm is proposed to optimize weights of document keywords for auto-reply accuracy. The proposed TCDE algorithm combines the use of differential evolution for exploring the optimal feasible region in macro-space with the use of the Taguchi method for exploiting the optimal solution in micro-space. For learning purpose, an answer needs to be exactly given for a specific query. Notably, teachers give a problem answer to elementary students who need to have the clear and accurate solution for learning according to their queries. This study shows the TCDE which integrates a cosine similarity measure and an evaluation function to successfully find the best weights of document keywords for auto-reply accuracy. Performance comparisons confirm that the TCDE algorithm outperforms existing methods presented in the literature in finding the best weights of document keywords and obtaining accurate answers.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2013.07.045