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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 12 Documents
 1   2 
Search results for , issue "Vol 6, No 3: September 2017" : 12 Documents clear
An Accurate Facial Component Detection Using Gabor Filter K. Sudhakar; P. Nithyanandam
Bulletin of Electrical Engineering and Informatics Vol 6, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (508.309 KB) | DOI: 10.11591/eei.v6i3.683

Abstract

Face detection is a critical task to be resolved in a variety of applications. Since faces include various expressions it becomes a difficult task to detect the exact output. Face detection not only play a main role in personal identification but also in various fields which includes but not limited to image processing, pattern recognition, graphics and other application areas. The proposed system performs the face detection and facial components using Gabor filter. The results show accurate detection of facial components
Context Based Classification of Reviews Using Association Rule Mining, Fuzzy Logics and Ontology Razia Sulthana A; Subburaj Ramasamy
Bulletin of Electrical Engineering and Informatics Vol 6, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (466.504 KB) | DOI: 10.11591/eei.v6i3.682

Abstract

The Internet has facilitated the growth of recommendation system owing to the ease of sharing customer experiences online. It is a challenging task to summarize and streamline the online textual reviews. In this paper, we propose a new framework called Fuzzy based contextual recommendation system. For classification of customer reviews we extract the information from the reviews based on the context given by users. We use text mining techniques to tag the review and extract context. Then we find out the relationship between the contexts from the ontological database. We incorporate fuzzy based semantic analyzer to find the relationship between the review and the context when they are not found therein. The sentence based classification predicts the relevant reviews, whereas the fuzzy based context method predicts the relevant instances among the relevant reviews. Textual analysis is carried out with the combination of association rules and ontology mining. The relationship between review and their context is compared using the semantic analyzer which is based on the fuzzy rules.

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