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Recommender systems are being improved by every means to be more accurate, more robust, and faster. Collaborative filtering is the mainstream type of recommendation algorithms, and its core is calculating the similarity between users or items based on ratings. Researchers recently found that the binary similarity based solely on who-rated-what rather than(More)
Gender issues are studied in depth with the case study and survey. Balanced gender ratio, significant gender divergence in the relevance of employment and major, gender balance in competency, gender difference in learning styles, gender imbalance in perception of women's fitness in information industry, gender bias in major interest and employment(More)
Learning styles of computer majors are measured by amended Memletics-Learning-Styles-Inventory. The Independent-Samples T Test is used to test the hypothesis that female students differ from male students in their learning styles. Quantitative analysis showed that female students score higher in logical dimension, lower in social and solitary dimensions,(More)
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