Soft Computing, Artificial Intelligence and Applications

Gradient Omissive Descentis A Minimization Algorithm Gustavo A. Lado and Enrique C. Segura Universidad de Buenos Aires Cyprus ABSTRACT This article presents a promising new gradient-based backpropagation algorithm for multi-layer feedforward networks. The method requires no manual selection of global hyperparameters and is capable of dynamic local adaptations using only first-order information at a low computational cost. Its semi-stochastic nature makes it fit for mini-batch training and robust to different architecture choices and data distributions. Experimental evidence shows that the proposed algorithm improves training in terms of both convergence rate and speed as compared with other well known techniques. KEYWORDS Neural Networks, Backpropagation, Cost Function Minimization Original Source URL: http://aircconline.com/ijscai/V8N1/8119ijscai03.pdf http://airccse.org/journal/ijscai/current2019.html

Innovative Bi Approaches and Methodologies Implementing A Multilevel Analytics Platform Based on Data Mining and Analytical Models: A Case of Study in Roadside Assistance Services Alessandro Massaro, Angelo Leogrande, Palo Lisco, Angelo Galiano and Nicola Savino Dyrecta Lab, IT Research Laboratory, Italy. ABSTRACT The paper proposes an advanced Multilevel Analytics Model –MAM-, applied on a specific case of study referring to a research project involving an industry mainly working in roadside assistance service (ACI Global S.p.A.). In the first part of the paper are described the initial specifications of the research project by addressing the study on information system architectures explaining knowledge gain, decision making and data flow automatism applied on the specific case of study. In the second part of the paper is described in details the MAM acting on different analytics levels, by describing the first analyzer module and the second one involving data mining ...

Deep Learning Sentiment Analysis of Amazon.Com Reviews and Ratings Nishit Shrestha and Fatma Nasoz University of Nevada Las Vegas, USA ABSTRACT Our study employs sentiment analysis to evaluate the compatibility of Amazon.com reviews with their corresponding ratings. Sentiment analysis is the task of identifying and classifying the sentiment expressed in a piece of text as being positive or negative. On e-commerce websites such as Amazon.com, consumers can submit their reviews along with a specific polarity rating. In some instances, there is a mismatch between the review and the rating. To identify the reviews with mismatched ratings we performed sentiment analysis using deep learning on Amazon.com product review data. Product reviews were converted to vectors using paragraph vector, which then was used to train a recurrent neural network with gated recurrent unit. Our model incorporated both semantic relationship of review text and product information. We also developed a w...

Bacteria Identification From Microscopic Morphology: A Survey Noor Amaleena Mohamad, Noorain Awang Jusoh, Zaw Zaw Htike and Shoon Lei Win International Islamic University Malaysia, Malaysia ABSTRACT Great knowledge and experience on microbiology are required for accurate bacteria identification. Automation of bacteria identification is required because there might be a shortage of skilled microbiologists and clinicians at a time of great need. There have been several attempts to perform automatic background identification. This paper reviews state-of-the-art automatic bacteria identification techniques. This paper also provides discussion on limitations of state-of-the-art automatic bacteria identification systems and recommends future direction of automatic bacteria identification. KEYWORDS Bacteria Identification, Cocci,Bacilli, Vibrio, Naïve Bayes, Machine Learning Original Source URL: http://airccse.org/journal/ijscai/papers/3214ijscai01.pdf http://airccse.org/journal...