Machine Learning Techniques for Code Smell Detection: A Systematic Literature Review and Meta-Analysis Muhammad Ilyas Azeem a,b, Fabio Palombad, Lin Shi , Qing Wanga,b,c aLaboratory for Internet Software Technologies, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China. Teaching and Learning: A Rapid Review of the Literature Emily Quinan, Stephen Anderson & Karen Mundy Ontario Institute for Studies in Education University of Toronto June 1014 A joint initiative between the Aga Khan Foundation Canada (AKFC) and the Government of Canada, through the Department of Foreign Affairs, Trade and Development (DFATD). The purpose of the systematic review was to analyze scholarly articles that were published between 2015 and 2018 addressing or implementing supervised and unsupervised machine learning techniques in different problem-solving paradigms. Students in my Stanford courses on machine learning have already made several useful suggestions, as have my colleague, Pat Langley, and my teaching Section 3 reviews the various techniques, methods and models used in the prognosis of bearing till date. Machine learning (ML) is transforming all areas of science. 25, 80805 Munich, Germany Index Terms— Text mining, Web mining, Documents classification, Information retrieval. In section III, we did research ... Machine learning approach can be used for analyzing sentiments from the text. To extend the research on the role of learner control in e‐learning and to examine its impact on e‐learning effectiveness, this study reviews 54 empirical articles on learner control during the period 1996–2013. It was concluded that the research theme is still relevant and that the use of data from developing markets is a research opportunity. endobj In 2004 IEEE International Joint Conference on Neural Networks, 2004. Machine Learning in Banking Risk Management: A Literature Review Martin Leo * , Suneel Sharma and K. Maddulety SP Jain School of Global Management, ... To determine the risks specific to banks, as an alternate to leveraging the existing literature, a review was done of bank annual reports. Becta | Learning styles – an introduction to the research literature 4. Machine learning is as growing as fast as concepts such as Big data and the field of data science in general. AI is efficient and scalable [11] and provides capabilities to enable a machine to process more BLENDED LEARNING: LITERATURE REVIEW! Unstructured data remains a challenge in almost all data intensive application fields such as business, universities, research institutions, government funding agencies, and technology intensive companies (Khan, Baharudin, Lee, &Khan, 2010). I. 985–990). 2. Organizational Learning: A Literature Review Brenda Barker Scott, MIR, Ph.D Candidate Facilitator, Queen’s University IRC Published: January 2011 IRC Research Program irc.queensu.ca #-Ogaiai Leaig-BB Ce_La 1 11-01-13 2:58 PM Page 1 and industrial analysts, we perform a systematic literature review of machine learning applications in baseball analytics. Instead, my goal is to give the reader su cient preparation to make the extensive literature on machine learning accessible. A systematic literature review on machine learning applications for consumer sentiment analysis using online reviews Praphula Kumar Jain 1; and Rajendra Pamula 1 Indian Institute of Technology (Indian School of Mines), Dhanbad-826004, JH, INDIA Abstract Consumer sentiment analysis is a recent fad for social media related applica- 2 0 obj Computer Science Engineering . 2015) wrote a review paper that did a … Overview of this literature review In section 1, common educational objectives across national and … AMC Engineering College . Based on the abstracts, a … Culture Learning in Language Education: A Review of the Literature R. Michael Paige, Helen Jorstad, Laura Siaya, Francine Klein, Jeanette Colby INTRODUCTION This paper examines the theoretical and research literatures pertaining to culture learning in language education programs. MYRA G. FLORES et al: LITERATURE REVIEW OF AUTOMATED WASTE SEGREGATION SYSTEM USING . can facilitate explanations in Machine Learning systems. The most commonly used models for prediction involve support vector machines (SVMs) and neural networks. The approaches employed in literature fall mainly under three problem class umbrellas: Regression, Binary Classi cation, and Multiclass Classi cation. Proceedings . vol. Optical character recognition is a science that enables to translate various types of documents or images into analyzable, editable and searchable data. As such, an overview of the different steps of a systematic review (as introduced in Tsafnat et al., 2014) is given, along with possible ways for automation. . The approaches employed in literature fall mainly under three problem class umbrellas: Regression, Binary Classi cation, and Multiclass Classi cation. x��=koG���?�S@�x�93��p�cm�{�؛�b�8P�X暖����G���\WU?�g�3�.��䰟������/��������x�b��\|�/������}������^o�ۛ��o�����~s�ߝ�,N�{�8}��W��Ģ�:�x���Ģv����*-���le�ŻO_U/��������Vk��^�徿[�5~�YVk�З���i�n��Y>��w���x�j����+!����춫u��/W���+�ݯ����?����W��`aݲv7|��>}3� In this paper, various machine learning algorithms have been discussed. Both discriminative and generative methods are considered ... 3 Conclusions from literature review 32 4 Generative machine learning research 34 4.1 Switching Autoregressive Hidden Markov Models . DOI 10.5013/IJSSST.a.20.S2.15 15.1 ISSN: 1473-804x online, 1473-8031 print Literature Review of Automated Waste Segregation System using Machine Learning: A Comprehensive Analysis The machine learning classifiers for Web Spam detection are: ವ Support Vector Machine (SVM) - SVM 19 discriminates a set of high-dimension features using a or sets of hyperplanes that gives the largest minimum distance to separates all data points among classes. With the high productivity in the machine learning area applied to the prediction of financial market prices, objective methods are required for a consistent analysis of the most relevant bibliography on the subject. These algorithms are used for various purposes like data mining, image processing, predictive analytics, etc. The prices of financial assets are non-linear, dynamic, and chaotic; thus, they are financial time series that are difficult to predict. <>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/Annots[ 11 0 R 12 0 R 18 0 R 31 0 R 32 0 R 33 0 R 34 0 R 35 0 R 36 0 R 37 0 R 38 0 R 39 0 R 40 0 R 41 0 R 42 0 R 43 0 R 44 0 R 45 0 R 46 0 R 47 0 R 48 0 R 49 0 R 50 0 R 51 0 R 52 0 R 53 0 R 54 0 R 55 0 R 56 0 R 57 0 R] /MediaBox[ 0 0 595.44 841.68] /Contents 4 0 R/StructParents 0>> machine learning, enabled (partially) automated literature reviews to become technically feasible. Literature review: Machine learning techniques applied to financial market prediction. The complex and time-consuming calculations in molecular simulations are particularly suitable for an ML revolution and have already been profoundly affected by the application of existing ML methods. Approaches to learning: Literature review 2 Some of the sources were obtained through the snowballing method by checking the references lists of the existing sources. Given the ubiquity of handwritten documents in human transactions, Optical Character Recognition (OCR) of documents have invaluable practical worth. Semantic Web Technologies for Explainable Machine Learning Models: A Literature Review Arne Seeliger 1;2 (B), Matthias Pfa , and Helmut Krcmar2 1 fortiss, Research Institute of the Free State of Bavaria associated with Technical University of Munich, Guerickestr. 16 . Article contents; Figures & tables; Video; Audio; Supplementary Data; Cite. to name a few. Machine learning (ML) is rapidly revolutionizing many fields and is starting to change landscapes for physics and chemistry. the book is not a handbook of machine learning practice. Sometimes after viewing the data, we cannot interpret the pattern or extract information from the data. The original ELM model has been equipped with various extensions to make it more suitable and efficient for specific applications. <> To address this topic, we present current approaches of combining Machine Learning with Semantic Web Technologies in the context of model explainability based on a systematic literature review. The main advantage of using machine learning is that, once an algorithm learns what to do with data, it can do its work automatically. to the use of machine learning techniques for literature reviews and systematic reviews in EFSA. SUPERVISED MACHINE LEARNING: A REVIEW OF... Informatica 31 (2007) 249–268 251 not being used, a larger training set is needed, the dimensionality of the problem is too high, the selected ... the literature. Literature Survey on Sentiment Analysis of Twitter Data using Machine Learning ... has discussed sentiment analysis on the customer’s review using classification. This section displays the discoveries from the literature review process that was explained in the earlier sections. Heritage, Kim, Vendlinski, and Herman (2009) explain that learning progressions are important to the Among the latest techniques, machine learning models are some of the most researched, given their capabilities for recognizing complex patterns in various applications. Literature published within the past ten years was prioritized. Literature Review ... machine-learning and other statistical techniques can be used to make underwriting more targeted and efficient. Literature Review on Machine Learning in Supply Chain Management 415 term "Supply Chain Management [AND] Machine Learning". It selects hidden nodes randomly and analytically determines their output weight. %���� 4 0 obj endobj The authors of (Huang et al. There have been a host of algorithms and applications for learning with queries over the years, and this document is an attempt to distill the core ideas, methods, and applications that have been considered by the machine learning community. This report provides a general review of the literature on active learning. The dataset consisted of 98 electronic materials (research articles, review articles, thesis as well as e-books on machine learning and predictive models). CONTENT ... e-learning and blended learning, but it already started much earlier (Moore & Kearsely, 2011, as cited in Güzer & Caner, 2014). Literature Review Assessment for Learning/ Formative Assessment lowaCORE Q Lit Review: ... learning goal as well as provide a map of future learning opportunities. Though there is voluminous literature stating the capabilities of different types of text classification techniques, the spread of these techniques in advanced fields like Artificial Intelligence (AI)/Machine Learning (ML) is seldom reported. © 2019 Elsevier Ltd. All rights reserved. . By examining academic articles, policy papers, news articles, and position papers from across the globe, this literature review aims to provide an overview of AI from multiple perspectives. This paper provides a review of the theory and methods of document classification and text mining, focusing on the existing litera-ture. … In this paper, various machine learning algorithms have been discussed. Bangalore . To Conclusions regarding the impact of AI on actuarial work In the literature review sections, wewill first describe the historical challenges driving different types of actuarial before approaches moving on review the to machine learning … ... A Chrome extension that boost your paper writing (especially the literature review part). learning outcome, satisfaction, student retention et cetera. The following section briefly presents a review of the main machine learning techniques covered in the articles selected for this study. Our target is mapping the state of art of fake news detection, defining fake news and finding the most useful machine learning technique for doing so. Conclusions regarding the impact of AI on actuarial work In the literature review sections, wewill first describe the historical challenges driving different types of actuarial before approaches moving on review the to machine learning … Literature Review on Machine Learning in Supply Chain Management 415 term "Supply Chain Management [AND] Machine Learning". Learning styles and learning strategies A significant number of theorists and researchers (Kolb, Honey and Mumford, for instance) have argued that learning styles are not determined by … learning accuracy, least human invention, and fast learning speed (as demonstrated in Fig. Machine learning is used to teach machines how to handle the data more efficiently. Use of P ropofol and emergence agitation in children: A literature review . Abstract— There is an endless exciting new research in the field of Artificial Intelligence; this review is far from a global Through a systematic literature review method, in this work we searched classical electronic libraries in order to find the most recent papers related to fake news detection on social medias. A literature review summarizes and synthesizes the existing scholarly research on a particular topic. Literature reviews are a form of academic writing commonly used in the sciences, social sciences, and humanities. Unlike other review papers such as [9]–[11], the presentation aims at highlighting conditions under which the use of machine learning is justified in engineering problems, as well as specific classes of learning algorithms that are Fifty-seven texts were reviewed, and a classification was proposed for markets, assets, methods, and variables. However, unlike research papers, which establish new arguments and make original contributions, literature reviews organize and present existing research. PDF; Split View Views. Cite. Copyright © 2020 Elsevier B.V. or its licensors or contributors. Learning Organisations: A Literature Review and Critique Steven Talbot, Christina Stothard, Maya Drobnjak and Denise McDowall Land Division Defence Science and Technology Organisation DSTO-TR-2928 ABSTRACT A literature review on the Learning Organisation field … the last few years, deep learning, the state-of-the-art machine learning technique utilized in many complex tasks, has been employed in recommender systems to improve the quality of recommendations. . 2 (pp. E-Learning Literature Review In: Computers and Technology Submitted By amekitmfon Words 16343 Pages 66. e-learning - A Review of Literature Prepared by Tim L. Wentling Consuelo Waight James Gallaher Jason La Fleur Christine Wang Alaina Kanfer Knowledge and Learning Systems Group . Literature reviews of how AI can be used in different lines of actuarial work 3. Machine Learning: A Constraint-Based Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines.. action learning, systematic literature review, human resource development No learning without action and no action without learning. The search for models to predict the prices of financial markets is still a highly researched topic, despite major related challenges. and industrial analysts, we perform a systematic literature review of machine learning applications in baseball analytics. stream In AI 2.0, machine learning (ML) forms a typical representative algorithm category used to achieve predictions and judgments by analyzing and learning from massive amounts of historical and synthetic data to help people make optimal decisions. 1 0 obj ScienceDirect ® is a registered trademark of Elsevier B.V. ScienceDirect ® is a registered trademark of Elsevier B.V. Based on the review… Data mining is one amid the core research areas in the field of computer science. A literature review is a survey of scholarly sources that provides an overview of statement or the study’s goals or purpose. A Literature Survey on Artificial Intelligence . In this review of the literature on e-learning, we present and discuss definitions of e-learning, hybrid learning and blended learning, and we review the literature comparing different online teaching formats with traditional on-campus/face-to-face teaching. ... ranks articles by relevance to improve screening efficiency, download full-text pdf of research articles in batch. Literature reviews of how AI can be used in different lines of actuarial work 3. 2!! These algorithms are used for various purposes like data mining, image processing, predictive analytics, etc. 3 0 obj With its ability to solve complex tasks autonomously, ML is being exploited as a radically new way to help find material correlations, understand materials chemistry, and accelerate the discovery of materials. Search Procedure From the end of March to May 2013 we searched published academic and professional scholarship using search words that included authentic intellectual work, inquiry-based learning, project-based learning, problem-based learning, and design-based learning. INTRODUCTION The text mining studies are gaining more importance re- I. NTRODUCTION. Due to the re-cent developments in ML, the results were restricted to publications from 2009-2019. machine-learning awesome deep-learning graph awesome-list defense robustness literature-review adversarial-examples adversarial-attacks graph … Understanding and analyzing existing literature on AI is a necessary precursor to subsequently recommending policy on the matter. AI is … Many industries In that case, we apply machine learning [1]. endobj This literature review is organized as follows: section 2 discusses the meaning of bearing prognosis and classification of various prognosis methods. Extreme Learning Machines (ELM) were suggested as alternative learning algorithms instead of FFNN. Further, reviewing text classification approaches from an algo- learning spaces promote collaboration and participatory learning between and among students, and between students and teachers. S S symmetry Article Machine Learning and Big Data in the Impact Literature. The real starting point occurred through letter correspondence between teacher and student. *This sample paper was adapted by the Writing Center from Key, K.L., Rich, C., DeCristofaro, C., Collins, S. (2010). We use cookies to help provide and enhance our service and tailor content and ads. <> https://doi.org/10.1016/j.eswa.2019.01.012. (PDF) A SYSTEMATIC LITERATURE REVIEW OF MACHINE LEARNING TECHNIQUE USAGE | Arrahman Adnani - Academia.edu The development of machine learning technique is very fast now. Approaches to learning: Literature review 2 Some of the sources were obtained through the snowballing method by checking the references lists of the existing sources. Yet there is a knowledge data detection process helps the data mining to extract hidden information from the dataset there is a big scope of machine learning Among the main results, of particular note is the greater number of studies that use data from the North American market. The machine learning area applied to the prediction of financial market prices. Learning Analytics Methods, Benefits, and Challenges in Higher Education: A Systematic Literature Review John T. Avella, Mansureh Kebritchi, Sandra G. Nunn, Therese Kanai University of Phoenix Abstract Higher education for the 21st century continues to promote discoveries in the field through learning … Keywords classification, machine learning, statistical methods, analysis. The prices are financial time series that are difficult to predict. 2. Paper reading notes on Deep Learning and Machine Learning. to name a few. representation and machine learning techniques. However, conceptual work on the role of learner control in e‐learning has not advanced sufficiently to predict how autonomous learning impacts e‐learning effectiveness. 1.4 Structure of the literature review..... 3 2. However, in practice there is always certain sensitivity to the partitioning used. Abstract. The former is characterised by single-hidden layer feedforward neural networks (SLFN). This review aims to, first, present a short . 12 In an article on The Latest Trends in Classroom Design, Winske discusses how educators now flip their classrooms, encourage 2. %PDF-1.4 By continuing you agree to the use of cookies. Its usage has spread to various fields, such as learning machines currently used in medical science, pharmacology, agriculture, archeology, games, business and so forth. Section 4 concludes the literature review with summary and future research directions. The literature review is a method for investigating the approaches of a studied topic, as stated by Lage Junior and Godinho Filho (2010, p. 14). AI is a sub-field of computer science containing techniques such as machine learning, deep learning, and natural language processing to enable intelligent machines [17, 29].

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