• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 12 matches

• 2020
• 
  Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Stefano Pascolutti, Giovanni Ponti:
  Mining Data for Financial Applications - 4th ECML PKDD Workshop, MIDAS 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers. Lecture Notes in Computer Science 11985, Springer 2020, ISBN 978-3-030-37719-9 [contents]
• 2019
• 
  Tesi Aliaj, Aris Anagnostopoulos, Stefano Piersanti:
  Firms Default Prediction with Machine Learning. MIDAS@PKDD 2019: 47-59
• 
  Argimiro Arratia, Eduardo Sepúlveda:
  Convolutional Neural Networks, Image Recognition and Financial Time Series Forecasting. MIDAS@PKDD 2019: 60-69
• 
  Luca Barbaglia, Sergio Consoli, Sebastiano Manzan:
  Monitoring the Business Cycle with Fine-Grained, Aspect-Based Sentiment Extraction from News. MIDAS@PKDD 2019: 101-106
• 
  Rafaël Van Belle, Sandra Mitrovic, Jochen De Weerdt:
  Representation Learning in Graphs for Credit Card Fraud Detection. MIDAS@PKDD 2019: 32-46
• 
  Saumya Bhadani, Ishan Verma, Lipika Dey:
  Mining Financial Risk Events from News and Assessing their Impact on Stocks. MIDAS@PKDD 2019: 85-100
• 
  Jérémy Charlier, Gaston Ormazabal, Radu State, Jean Hilger:
  MQLV: Optimal Policy of Money Management in Retail Banking with Q-Learning. MIDAS@PKDD 2019: 1-15
• 
  Xiangru Fan, Xiaoqian Wei, Di Wang, Wen Zhang, Wu Qi:
  Multi-step Prediction of Financial Asset Return Volatility Using Parsimonious Autoregressive Sequential Model. MIDAS@PKDD 2019: 107-121
• 
  Thomas Kellermeier, Tim Repke, Ralf Krestel:
  Mining Business Relationships from Stocks and News. MIDAS@PKDD 2019: 70-84
• 
  Allison Koenecke, Amita Gajewar:
  Curriculum Learning in Deep Neural Networks for Financial Forecasting. MIDAS@PKDD 2019: 16-31
• 
  Luca Tiozzo Pezzoli, Sergio Consoli, Elisa Tosetti:
  Big Data Financial Sentiment Analysis in the European Bond Markets. MIDAS@PKDD 2019: 122-126
• 
  Giuseppe Santomauro, Daniela Alderuccio, Fiorenzo Ambrosino, Andrea Fronzetti Colladon, Silvio Migliori:
  A Brand Scoring System for Cryptocurrencies Based on Social Media Data. MIDAS@PKDD 2019: 127-132