Results 211 to 220 of about 8,190 (251)

Conjunctive combined causal rules mining

2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 2015
Causal discovery is a well-studied problem due to an urgent need for systems that predict, explain, and make proper and necessary decisions in many domains including epidemiology, biology, medicine, economics, physics, and social sciences. Existing techniques such as learning Bayesian networks (BNs) and Randomized controlled trials (RCTs) are expensive
Manal Alharbi, Sanguthevar Rajasekaran
openaire   +1 more source

A Causal Approach for Mining Interesting Anomalies

2013
We propose a novel approach which combines the use of Bayesian network and probabilistic association rules to discover and explain anomalies in data. The Bayesian network allows us to organize information in order to capture both correlation and causality in the feature space, while the probabilistic association rules have a structure similar to ...
Sakshi Babbar, Didi Surian, Sanjay Chawla   +2 more
openaire   +1 more source

Multisource causal data mining

SPIE Proceedings, 2012
Analysts are faced with mountains of data, and finding that relevant piece of information is the proverbial needle in a haystack, only with dozens of haystacks. Analysis tools that facilitate identifying causal relationships across multiple data sets are sorely needed. 21st Century Systems, Inc.
Robert Woodley, Michael Gosnell, Kevin Shallenberger   +2 more
openaire   +1 more source

Pairwise Causality Structure: Towards Nested Causality Mining on Financial Statements

2020
Causality mining, which aims to find cause-effect relations in text, is an important yet challenging problem in natural language understanding. The extraction of causal relations is beneficial to practitioners in document-intensive industries.
Dian Chen 0002, Yixuan Cao 0001, Ping Luo 0001   +2 more
openaire   +1 more source

A Method for Mining Granger Causality Relationship on Atmospheric Visibility

ACM Transactions on Knowledge Discovery From Data, 2021
Atmospheric visibility is an indicator of atmospheric transparency and its range directly reflects the quality of the atmospheric environment. With the acceleration of industrialization and urbanization, the natural environment has suffered some damages. In recent decades, the level of atmospheric visibility shows an overall downward trend.
Bo Liu 0024, Xi He, Mingdong Song, Jianqiang Li 0002, Guangzhi Qu, Jianlei Lang, Rentao Gu   +6 more
exaly   +2 more sources

Imprecise Causality in Mined Rules

2007
Causality occupies a central position in human reasoning. It plays an essential role in commonsense decision-making. Data mining hopes to extract unsuspected information from very large databases. The results are inherently soft or fuzzy as the data is generally both incomplete and inexact. The best known data mining methods build rules.
openaire   +1 more source

Causal Deviance Mining

Deviance Mining aims to uncover the underlying reasons for deviant executions in business processes by analyzing their event logs. Existing approaches primarily rely on predictive techniques such as decision tree mining and rule mining to identify factors that explain deviations.
Rik Eshuis, Laura Genga, Rowan Griffioen
openaire   +2 more sources

Mining Causality for Explanation Knowledge from Text

Journal of Computer Science and Technology, 2007
Mining causality is essential to provide a diagnosis. This research aims at extracting the causality existing within multiple sentences or EDUs (Elementary Discourse Unit). The research emphasizes the use of causality verbs because they make explicit in a certain way the consequent events of a cause, e.g., “Aphids suck ...
Chaveevan Pechsiri, Asanee Kawtrakul
openaire   +1 more source

Mining Medical Causality for Diagnosis Assistance

Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017
In the medical context, causal knowledge usually refers to causal relations between diseases and symptoms, living habits and diseases, symptoms which get better and therapy, drugs and side-effects, etc [3]. All these causal relations are usually in medical literature, forum and clinical cases and compose the core part of medical diagnosis.
openaire   +1 more source

Dependency mining-based causal message logging

Information Processing Letters, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yiwei Ci, Zhan Zhang 0002, De-Cheng Zuo, Zhibo Wu, Xiao-Zong Yang   +4 more
openaire   +1 more source