Download or read book Data Mining and Knowledge Discovery for Big Data written by Wesley W. Chu and published by Springer Science & Business Media. This book was released on 2013-09-24 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease. Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation. The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.
Download or read book Aspect based Opinion Mining in Online Reviews written by Samaneh Abbasi Moghaddam and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Other people's opinions are important piece of information for making informed decisions. Today the Web has become an excellent source of consumer opinions. However, as the volume of opinionated text is growing rapidly, it is getting impossible for users to read all reviews to make a good decision. Reading different and possibly even contradictory opinions written by different reviewers even make them more confused. In the same way, monitoring consumer opinions is getting harder for the manufactures and providers. These needs have inspired a new line of research on mining customer reviews, or opinion mining. Aspect-based opinion mining, is a relatively new sub-problem that attracted a great deal of attention in the last few years. Extracted aspects and estimated ratings clearly provides more detailed information for users to make decisions and for suppliers to monitor their consumers. In this thesis, we address the problem of aspect-based opinion mining and seek novel methods to improve limitations and weaknesses of current techniques. We first propose a method, called Opinion Digger, that takes advantages of syntactic patterns to improve the accuracy of frequency-based technique. We then move on to model-based approaches and propose an LDA-based model, called ILDA, to jointly extract aspects and estimate their ratings. In our next work, we compare ILDA with a series of increasingly sophisticated LDA models representing the essence of the major published methods in the literature. A comprehensive evaluation of these models indicates that while ILDA works best for items with large number of reviews, it performs poorly when the size of the training dataset is small, i.e., for cold start items. The cold start problem is critical as in real-life data sets around 90% of items are cold start. We address this problem in our last work and propose a LDA-based model, called FLDA. It models items and reviewers by a set of latent factors and learns them using reviews of an item category. Experimental results on real life data sets show that FLDA achieve significant gain for cold start items compared to the state-of-the-art models.
Download or read book Sentiment Analysis and Opinion Mining written by Bing Liu and published by Springer Nature. This book was released on 2022-05-31 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography
Download or read book Sentiment Analysis and Opinion Mining written by Bing Liu and published by Morgan & Claypool Publishers. This book was released on 2012 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography
Download or read book Aspect based Opinion Mining from Online Customer Reviews Using Word Embeddings written by Alin Secareanu and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Opinion Mining and Sentiment Analysis written by Bo Pang and published by Now Publishers Inc. This book was released on 2008 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.
Download or read book Progress in Artificial Intelligence written by Eugénio Oliveira and published by Springer. This book was released on 2017-08-09 with total page 895 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 18th EPIA Conference on Artificial Intelligence, EPIA 2017, held in Porto, Portugal, in September 2017. The 69 revised full papers and 2 short papers presented were carefully reviewed and selected from a total of 177 submissions. The papers are organized in 16 tracks devoted to the following topics: agent-based modelling for criminological research (ABM4Crime), artificial intelligence in cyber-physical and distributed embedded systems (AICPDES), artificial intelligence in games (AIG), artificial intelligence in medicine (AIM), artificial intelligence in power and energy systems (AIPES), artificial intelligence in transportation systems (AITS), artificial life and evolutionary algorithms (ALEA), ambient intelligence and affective environments (AmIA), business applications of artificial intelligence (BAAI), intelligent robotics (IROBOT), knowledge discovery and business intelligence (KDBI), knowledge representation and reasoning (KRR), multi-agent systems: theory and applications (MASTA), software engineering for autonomous and intelligent systems (SE4AIS), social simulation and modelling (SSM), and text mining and applications (TeMA).
Download or read book Natural Language Annotation for Machine Learning written by James Pustejovsky and published by "O'Reilly Media, Inc.". This book was released on 2013 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Includes bibliographical references (p. 305-315) and index.
Download or read book Proceedings of International Ethical Hacking Conference 2018 written by Mohuya Chakraborty and published by Springer. This book was released on 2018-10-04 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the implications of new technologies for a secured society. As such, it reflects the main focus of the International Conference on Ethical Hacking, eHaCon 2018, which is essentially in evaluating the security of computer systems using penetration testing techniques. Showcasing the most outstanding research papers presented at the conference, the book shares new findings on computer network attacks and defenses, commercial security solutions, and hands-on, real-world security experience. The respective sections include network security, ethical hacking, cryptography, digital forensics, cloud security, information security, mobile communications security, and cyber security.
Download or read book Sentiment Analysis written by Bing Liu and published by Cambridge University Press. This book was released on 2020-10-15 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and also new material on emotion and mood analysis techniques, emotion-enhanced dialogues, and multimodal emotion analysis.
Download or read book Advances in Computer Science and Ubiquitous Computing written by James J. Park and published by Springer. This book was released on 2017-12-19 with total page 1482 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the combined proceedings of the 12th KIPS International Conference on Ubiquitous Information Technologies and Applications (CUTE 2017) and the 9th International Conference on Computer Science and its Applications (CSA2017), both held in Taichung, Taiwan, December 18 - 20, 2017. The aim of these two meetings was to promote discussion and interaction among academics, researchers and professionals in the field of ubiquitous computing technologies. These proceedings reflect the state of the art in the development of computational methods, involving theory, algorithms, numerical simulation, error and uncertainty analysis and novel applications of new processing techniques in engineering, science, and other disciplines related to ubiquitous computing. James J. (Jong Hyuk) Park received Ph.D. degrees in Graduate School of Information Security from Korea University, Korea and Graduate School of Human Sciences from Waseda University, Japan. From December, 2002 to July, 2007, Dr. Park had been a research scientist of R&D Institute, Hanwha S&C Co., Ltd., Korea. From September, 2007 to August, 2009, He had been a professor at the Department of Computer Science and Engineering, Kyungnam University, Korea. He is now a professor at the Department of Computer Science and Engineering and Department of Interdisciplinary Bio IT Materials, Seoul National University of Science and Technology (SeoulTech), Korea. Dr. Park has published about 200 research papers in international journals and conferences. He has been serving as chair, program committee, or organizing committee chair for many international conferences and workshops. He is a steering chair of international conferences – MUE, FutureTech, CSA, CUTE, UCAWSN, World IT Congress-Jeju. He is editor-in-chief of Human-centric Computing and Information Sciences (HCIS) by Springer, The Journal of Information Processing Systems (JIPS) by KIPS, and Journal of Convergence (JoC) by KIPS CSWRG. He is Associate Editor / Editor of 14 international journals including JoS, JNCA, SCN, CJ, and so on. In addition, he has been serving as a Guest Editor for international journals by some publishers: Springer, Elsevier, John Wiley, Oxford Univ. press, Emerald, Inderscience, MDPI. He got the best paper awards from ISA-08 and ITCS-11 conferences and the outstanding leadership awards from IEEE HPCC-09, ICA3PP-10, IEE ISPA-11, PDCAT-11, IEEE AINA-15. Furthermore, he got the outstanding research awards from the SeoulTech, 2014. His research interests include IoT, Human-centric Ubiquitous Computing, Information Security, Digital Forensics, Vehicular Cloud Computing, Multimedia Computing, etc. He is a member of the IEEE, IEEE Computer Society, KIPS, and KMMS. Vincenzo Loia (BS ‘85, MS ‘87, PhD ‘89) is Full Professor of Computer Science. His research interests include Intelligent Agents, Ambient intelligence, Computational Intelligence. Currently he is Founder & Editor-in-chief of “Ambient Intelligence and Humanized Computing”, and Co-Editor-in-Chief of “Softcomputing”, Springer-Verlag. He is Chair of the Task Forces “Intelligent Agents” and “Ambient Intelligence” IEEE CIS ETTC. He has been Chair the Emergent Technical Committe "Emergent Technology", IEEE CIS Society and Vice-Chair of Intelligent Systems Applications Technical Committee. He has been author of more than 200 scientific works, Editor/co-editor of 4 Books, 64 journal papers, 25 book chapters, and 100 conference papers. He is Senior member of the IEEE, Associate Editor of IEEE Transactions on Industrial Informatics, and Associate Editor of IEEE Transactions on Systems, Man, and Cybernetics: Systems. Many times reviewers for national and international projects, Dr. Loia is active in the research domain of agents, ambient intelligence, computational intelligence, smartgrids, distributed platform for enrich added value. Gangman Yi in Computer Sciences at Texas A&M University, USA in 2007, and doctorate in Computer Sciences at Texas A&M University, USA in 2011. In May 2011, he joined System S/W group in Samsung Electronics, Suwon, Korea. He joined the Department of Computer Science & Engineering, Gangneung-Wonju National University, Korea, since March 2012. Dr. Yi has been researched in an interdisciplinary field of researches. His research focuses especially on the development of computational methods to improve understanding of biological systems and its big data. Dr. Yi actively serves as a managing editor and reviewer for international journals, and chair of international conferences and workshops. Yunsick Sung received his B.S. degree in division of electrical and computer engineering from Pusan National University, Busan, Korea, in 2004, his M.S. degree in computer engineering from Dongguk University, Seoul, Korea, in 2006, and his Ph.D. degree in game engineering from Dongguk University, Seoul, Korea, in 2012. He was employed as a member of the researcher at Samsung Electronics between 2006 and 2009. He was the plural professor at Shinheung College in 2009 and at Dongguk University in 2010. His main research interests are many topics in brain-computer Interface, programming by demonstration, ubiquitous computing and reinforcement learning. His Journal Service Experiences is Associate Editor at Human-centric Computing and Information Sciences, Springer (2015- Current).
Download or read book Learning and Collaboration Technologies written by Panayiotis Zaphiris and published by Springer. This book was released on 2015-07-18 with total page 749 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNCS volume 9192 constitutes the refereed proceedings of the Second International Conference on Learning and Collaboration Technologies, LCT 2015, held as part of the 17th International Conference on Human-Computer Interaction, HCII 2015, in Los Angeles, CA, USA in August 2015, jointly with 15 other thematically similar conferences. The total of 1462 papers and 246 posters presented at the HCII 2015 conferences were carefully reviewed and selected from 4843 submissions. These papers address addressing the following major topics: technology-enhanced learning, adaptive and personalised learning and assessment, virtual worlds and virtual agents for learning, collaboration and Learning Serious Games and ICT in education.
Download or read book Web Data Mining written by Bing Liu and published by Springer Science & Business Media. This book was released on 2011-06-25 with total page 637 pages. Available in PDF, EPUB and Kindle. Book excerpt: Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together to form an authoritative and coherent text. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.
Download or read book Intelligent Systems Technologies and Applications 2016 written by Juan Manuel Corchado Rodriguez and published by Springer. This book was released on 2016-09-19 with total page 1005 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the second International Symposium on Intelligent Systems Technologies and Applications (ISTA’16), held on September 21–24, 2016 in Jaipur, India. The 80 revised papers presented were carefully reviewed and selected from 210 initial submissions and are organized in topical sections on image processing and artificial vision, computer networks and distributed systems, intelligent tools and techniques and applications using intelligent techniques.
Download or read book Proceeding of the International Conference on Computer Networks Big Data and IoT ICCBI 2019 written by A. Pasumpon Pandian and published by Springer Nature. This book was released on 2020-03-04 with total page 1019 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the International Conference on Computing Networks, Big Data and IoT [ICCBI 2019], held on December 19–20, 2019 at the Vaigai College of Engineering, Madurai, India. Recent years have witnessed the intertwining development of the Internet of Things and big data, which are increasingly deployed in computer network architecture. As society becomes smarter, it is critical to replace the traditional technologies with modern ICT architectures. In this context, the Internet of Things connects smart objects through the Internet and as a result generates big data. This has led to new computing facilities being developed to derive intelligent decisions in the big data environment. The book covers a variety of topics, including information management, mobile computing and applications, emerging IoT applications, distributed communication networks, cloud computing, and healthcare big data. It also discusses security and privacy issues, network intrusion detection, cryptography, 5G/6G networks, social network analysis, artificial intelligence, human–machine interaction, smart home and smart city applications.
Download or read book Data Preprocessing in Data Mining written by Salvador García and published by Springer. This book was released on 2014-08-30 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data. This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying the techniques proposed in the specialized literature, is given.Each chapter is a stand-alone guide to a particular data preprocessing topic, from basic concepts and detailed descriptions of classical algorithms, to an incursion of an exhaustive catalog of recent developments. The in-depth technical descriptions make this book suitable for technical professionals, researchers, senior undergraduate and graduate students in data science, computer science and engineering.
Download or read book Sentiment Analysis of Product Reviews written by Chinmay Milind Suryavanshi and published by . This book was released on 2021 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital reviews play a critical role in improving global customer interaction and shaping consumer purchasing habits. E-commerce websites generate thousands of reviews about different products on their website. It is almost impossible to read and understand each review and it would take a considerable amount of man-force to decipher each review and understand customer's opinions. Sentiment Analysis is the process of identifying, extracting, and studying subjective knowledge using Natural Language Processing (NLP). In the context of product reviews, it involves studying consumer behavior to understand their shopping interests or patterns and then using that to understand their sentiment towards a product and manufacturer or a company. In the proposed work, over 20,000 reviews have been classified into positive and negative sentiments using Sentiment Analysis and machine learning. This model can then be used to predict the sentiment of the product review entered by the user. Logistic Regression, a linear implementation of Support Vector Machines called Linear Support Vector Classifier (LSVC) and Decision Tree algorithms have been used for the classification of reviews. The results show that the highest accuracy is achieved by Logistic Regression. The review can be entered by the user in our Graphical User Interface (GUI) which is then processed as input to our model which predicts the sentiment. The review along with its classified sentiment will be displayed to the user. The project also proposes an Aspect-Based sentiment analysis approach to extract the aspects or features of the product along with its associated opinion word, both of which are displayed on the command prompt. This Aspect-Based approach will help the business owner to extract the exact features loved or hated by the customers. The GUI is constructed using the Flask framework which uses Python programming language. This study shows that Logistic Regression has the highest accuracy compared to other algorithms.
