Mining Data for Financial Applications: 4th Ecml Pkdd Workshop, Midas 2019

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Last updated on Feb 23, 2025 10:58:07 PSTView all revisionsView all revisions

Item specifics

Condition
Like New: A book that looks new but has been read. Cover has no visible wear, and the dust jacket ...
Book Title
Mining Data For Financial Applications: 4Th Ecml Pkdd Worksh...
ISBN
9783030377199
Subject Area
Computers
Publication Name
Mining Data for Financial Applications : 4th ECML PKDD Workshop, MIDAS 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers
Publisher
Springer International Publishing A&G
Item Length
9.3 in
Subject
Hardware / General, Intelligence (Ai) & Semantics, Computer Vision & Pattern Recognition
Publication Year
2020
Series
Lecture Notes in Computer Science Ser.
Type
Textbook
Format
Trade Paperback
Language
English
Author
Ilaria Bordino
Item Weight
16 Oz
Item Width
6.1 in
Number of Pages
IX, 133 Pages
Category

About this product

Product Identifiers

Publisher
Springer International Publishing A&G
ISBN-10
3030377199
ISBN-13
9783030377199
eBay Product ID (ePID)
23038411463

Product Key Features

Number of Pages
IX, 133 Pages
Language
English
Publication Name
Mining Data for Financial Applications : 4th ECML PKDD Workshop, MIDAS 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers
Publication Year
2020
Subject
Hardware / General, Intelligence (Ai) & Semantics, Computer Vision & Pattern Recognition
Type
Textbook
Author
Ilaria Bordino
Subject Area
Computers
Series
Lecture Notes in Computer Science Ser.
Format
Trade Paperback

Dimensions

Item Weight
16 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Series Volume Number
11985
Number of Volumes
1 vol.
Illustrated
Yes
Table Of Content
MQLV: Optimal Policy of Money Management in Retail Banking with Q-Learning.- Curriculum Learning in Deep Neural Networks for Financial Forecasting.- Representation Learning in Graphs for Credit Card Fraud Detection.- Firms Default Prediction with Machine Learning.- Convolutional Neural Networks, Image Recognition and Financial Time Series Forecasting.- Mining Business Relationships from Stocks and News.- Mining Financial Risk Events from News and Assessing their impact on Stocks.- Monitoring the Business Cycle with Fine-grained, Aspect-based Sentiment Extraction from News.- Multi-step Prediction of Financial Asset Return Volatility Using Parsimonious Autoregressive Sequential Model.- Big Data Financial Sentiment Analysis in the European Bond Markets.- A Brand Scoring System for Cryptocurrencies Based on Social Media Data.
Synopsis
This book constitutes revised selected papers from the 4th Workshop on Mining Data for Financial Applications, MIDAS 2019, held in conjunction with ECML PKDD 2019, in Würzburg, Germany, in September 2019. The 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 16 submissions. They deal with challenges, potentialities, and applications of leveraging data-mining tasks regarding problems in the financial domain.
LC Classification Number
Q334-342

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