Sentiment Analysis Of Music Using Statistics And Machine Learning
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Sentiment Analysis Of Music Using Statistics And Machine Learning
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Author : Aakash Mukherjee
language : en
Publisher: Sanctum Books
Release Date : 2022-10-16
Sentiment Analysis Of Music Using Statistics And Machine Learning written by Aakash Mukherjee and has been published by Sanctum Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-16 with Music categories.
Sentiment analysis and prediction of contemporary Music can have a wide range of applications in modern society, for instance, selecting music for public institutions such as hospitals or restaurants to potentially improve the emotional well-being of personnel, patients, and customers respectively. In this project, a music recommendation system is built upon a Naive Bayes Classifier trained to predict the sentiment of songs based on song lyrics alone. Online streaming platforms have become one of the most important forms of music consumption. Most streaming platforms provide tools to assess the popularity of a song in the forms of scores and rankings. In this book, we address two issues related to song popularity. First, we predict whether an already popular song may attract higher-than-average public interest and become viral. Second, we predict whether sudden spikes in the public interest will translate into long-term popularity growth. We base our findings on data from the streaming platform Billboard, Spotify, and consider appearances in its "Most-Popular" list as indicative of popularity, and appearances in its "Virals" list as indicative of interest growth. We approach the problem as a classification task and employ a Support Vector Machine model built on popularity information to predict interest, and vice versa.
Music Data Mining
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Author : Tao Li
language : en
Publisher: CRC Press
Release Date : 2011-07-12
Music Data Mining written by Tao Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-12 with Business & Economics categories.
The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews. Bringing together an interdisciplinary array of top researchers, Music Data Mining presents a variety of approaches to successfully employ data mining techniques for the purpose of music processing. The book first covers music data mining tasks and algorithms and audio feature extraction, providing a framework for subsequent chapters. With a focus on data classification, it then describes a computational approach inspired by human auditory perception and examines instrument recognition, the effects of music on moods and emotions, and the connections between power laws and music aesthetics. Given the importance of social aspects in understanding music, the text addresses the use of the Web and peer-to-peer networks for both music data mining and evaluating music mining tasks and algorithms. It also discusses indexing with tags and explains how data can be collected using online human computation games. The final chapters offer a balanced exploration of hit song science as well as a look at symbolic musicology and data mining. The multifaceted nature of music information often requires algorithms and systems using sophisticated signal processing and machine learning techniques to better extract useful information. An excellent introduction to the field, this volume presents state-of-the-art techniques in music data mining and information retrieval to create novel ways of interacting with large music collections.
Sentiment Analysis
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Author : Bing Liu
language : en
Publisher: Cambridge University Press
Release Date : 2020-10-15
Sentiment Analysis written by Bing Liu and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-15 with Business & Economics categories.
A comprehensive introduction to computational analysis of sentiments, opinions, emotions, and moods. Now including deep learning methods.
Statistical Analysis Of Folk Songs Of Jharkhand
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Author : Shivani Tiwari
language : en
Publisher: Sanctum Books
Release Date : 2022-10-16
Statistical Analysis Of Folk Songs Of Jharkhand written by Shivani Tiwari and has been published by Sanctum Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-16 with Music categories.
Folk songs play a very significant role in Indian classical music as the root of Indian classical music is the Indian folk music itself. Different states have different folk songs. This work deals with the statistical analysis of the folk songs of Jharkhand. Each song's analysis concerns with verifying whether the probabilities of notes in the song are fixed throughout the song or are the note probabilities varying. This tells us whether the probability distribution followed by the notes is multinomial or quasi multinomial respectively. Statistical parameterization method is used to quantify melody and rhythm. The presence of rhythm and melody is also analyzed by the Inter Onset Interval (IOI) and note duration graphs. The book should be found useful by music researchers and students of music and musicology, ethnomusicologists and music enthusiasts.
Machine Learning And Music Generation
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Author : José M. Iñesta
language : en
Publisher: Routledge
Release Date : 2018-10-16
Machine Learning And Music Generation written by José M. Iñesta and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-16 with Mathematics categories.
Computational approaches to music composition and style imitation have engaged musicians, music scholars, and computer scientists since the early days of computing. Music generation research has generally employed one of two strategies: knowledge-based methods that model style through explicitly formalized rules, and data mining methods that apply machine learning to induce statistical models of musical style. The five chapters in this book illustrate the range of tasks and design choices in current music generation research applying machine learning techniques and highlighting recurring research issues such as training data, music representation, candidate generation, and evaluation. The contributions focus on different aspects of modeling and generating music, including melody, chord sequences, ornamentation, and dynamics. Models are induced from audio data or symbolic data. This book was originally published as a special issue of the Journal of Mathematics and Music.
Sentiment Analysis And Its Application In Educational Data Mining
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Author : Soni Sweta
language : en
Publisher: Springer Nature
Release Date :
Sentiment Analysis And Its Application In Educational Data Mining written by Soni Sweta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Music Data Analysis
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Author : Claus Weihs
language : en
Publisher: CRC Press
Release Date : 2016-11-17
Music Data Analysis written by Claus Weihs and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-17 with Business & Economics categories.
This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as chord and harmony, instrument and tempo recognition. It also discusses the implementation aspects of music data analysis such as architecture, user interface and hardware. It is ideal for use in university classes with an interest in music data analysis. It also could be used in computer science and statistics as well as musicology.
Sentiment Analysis Of English Tweets Using Data Mining
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Author : Dr. Gaurav Gupta
language : en
Publisher: BookRix
Release Date : 2018-03-26
Sentiment Analysis Of English Tweets Using Data Mining written by Dr. Gaurav Gupta and has been published by BookRix this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-26 with Technology & Engineering categories.
Due to the popularity of internet it becomes very easy for people to share their views over social networking websites. Most popular website among them is twitter. Twitter is a widely used social networking website that is used by the numerous people to give their opinion regarding a particular topic or product. So, today it becomes necessary to analyze the tweet of the people. The process to analyze and interpret the tweets is known as sentiment analysis. The main motive of this project is to identify how the tweets on the social networking website are used to identify the opinion of people regarding the particular product or policy. Twitter is a online website that allows the user to post the status of maximum 140 characters. Twitter has over 200 million registered users and 100 million active users [34]. So it comes to be a great source of valuable information. This project aims to develop a better way for sentiment analysis which is nothing a simple way to classify the tweets into positive, negative or neutral. The result of the sentiment analysis can be used by various organizations. Sentiment analysis can be used for forecasting the stock exchange, used to predict the popularity of any product in market, or used to predict the result of elections based on the public views on the social sites. The main motive of project is to develop a better way to accurately classify the unknown tweets according to their content.
Deep Learning Based Approaches For Sentiment Analysis
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Author : Basant Agarwal
language : en
Publisher: Springer Nature
Release Date : 2020-01-24
Deep Learning Based Approaches For Sentiment Analysis written by Basant Agarwal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-24 with Technology & Engineering categories.
This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge solutions for the most common and difficult challenges faced in sentiment analysis research. Providing detailed explanations of the methodologies, the book is a valuable resource for researchers as well as newcomers to the field.
Machine Learning Techniques For Text
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Author : Nikos Tsourakis
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-10-31
Machine Learning Techniques For Text written by Nikos Tsourakis and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-31 with Computers categories.
Take your Python text processing skills to another level by learning about the latest natural language processing and machine learning techniques with this full color guide Key FeaturesLearn how to acquire and process textual data and visualize the key findingsObtain deeper insight into the most commonly used algorithms and techniques and understand their tradeoffsImplement models for solving real-world problems and evaluate their performanceBook Description With the ever-increasing demand for machine learning and programming professionals, it's prime time to invest in the field. This book will help you in this endeavor, focusing specifically on text data and human language by steering a middle path among the various textbooks that present complicated theoretical concepts or focus disproportionately on Python code. A good metaphor this work builds upon is the relationship between an experienced craftsperson and their trainee. Based on the current problem, the former picks a tool from the toolbox, explains its utility, and puts it into action. This approach will help you to identify at least one practical use for each method or technique presented. The content unfolds in ten chapters, each discussing one specific case study. For this reason, the book is solution-oriented. It's accompanied by Python code in the form of Jupyter notebooks to help you obtain hands-on experience. A recurring pattern in the chapters of this book is helping you get some intuition on the data and then implement and contrast various solutions. By the end of this book, you'll be able to understand and apply various techniques with Python for text preprocessing, text representation, dimensionality reduction, machine learning, language modeling, visualization, and evaluation. What you will learnUnderstand fundamental concepts of machine learning for textDiscover how text data can be represented and build language modelsPerform exploratory data analysis on text corporaUse text preprocessing techniques and understand their trade-offsApply dimensionality reduction for visualization and classificationIncorporate and fine-tune algorithms and models for machine learningEvaluate the performance of the implemented systemsKnow the tools for retrieving text data and visualizing the machine learning workflowWho this book is for This book is for professionals in the area of computer science, programming, data science, informatics, business analytics, statistics, language technology, and more who aim for a gentle career shift in machine learning for text. Students in relevant disciplines that seek a textbook in the field will benefit from the practical aspects of the content and how the theory is presented. Finally, professors teaching a similar course will be able to pick pertinent topics in terms of content and difficulty. Beginner-level knowledge of Python programming is needed to get started with this book.