Conditional discriminative pattern mining: Concepts and algorithms

2017 ◽  
Vol 375 ◽  
pp. 1-15 ◽  
Author(s):  
Zengyou He ◽  
Feiyang Gu ◽  
Can Zhao ◽  
Xiaoqing Liu ◽  
Jun Wu ◽  
...  
Keyword(s):  
Pattern Mining ◽  
Discriminative Pattern

scholarly journals AN ARCHITECTURE-BASED TECHNIQUE TO MOBILE CONTACT RECOMMENDATION FOR EMERGENCY SITUATION IN NIGERIA

2016 ◽  
Vol 36 (1) ◽  
pp. 186-195
Author(s):  
BI Akigbe ◽  
RN Ikono ◽  
AO Ejidokun ◽  
SO Aderibigbe ◽  
BS Afolabi
Keyword(s):  
Recommendation System ◽  
Pattern Mining ◽  
Emergency Situation ◽  
Computing Platform ◽  
Emergency Situations ◽  
Inference Network ◽  
Algorithmic Technique ◽  
Smart Technologies ◽  
Close Relatives ◽  
Discriminative Pattern

Smart technologies such as smart phones, iPad and Tablets are ubiquitous in today’s society. They possess increasing computing and storage potentials. Thus, emerging as a dominant computing platform for different kinds of end-users. However, these technological possibilities have not been fully explored for emergency situations where close relatives must be contacted. This paper therefore presents an Emergency Contact Recommendation Model (ECRM) that was implemented into an emergency contact recommendation system. An architectural based approach was employed to highlight the contribution this paper made to extant knowledge. The leveraged of the Dust miner algorithmic technique, the direct discriminative pattern mining, and the Bayesian Inference Network technique were used to formulate the ECRM. The ECRM was implemented using the Java development and android tool kit. The model demonstrated commendable capabilities - considering the foregoing techniques when compared with what obtains in literature- to make useful recommendation in emergency situation(s) after implementation.   http://dx.doi.org/10.4314/njt.v36i124

scholarly journals Discriminative pattern mining and its applications in bioinformatics

2014 ◽  
Vol 16 (5) ◽  
pp. 884-900 ◽  
Author(s):  
Xiaoqing Liu ◽  
Jun Wu ◽  
Feiyang Gu ◽  
Jie Wang ◽  
Zengyou He
Keyword(s):  
Pattern Mining ◽  
Discriminative Pattern

scholarly journals Discriminative Pattern Mining for Breast Cancer Histopathology Image Classification via Fully Convolutional Autoencoder

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 36433-36445 ◽  
Author(s):  
Xingyu Li ◽  
Marko Radulovic ◽  
Ksenija Kanjer ◽  
Konstantinos N. Plataniotis
Keyword(s):  
Breast Cancer ◽  
Image Classification ◽  
Pattern Mining ◽  
Convolutional Autoencoder ◽  
Discriminative Pattern

An Adaptive Data Distribution Through Tree Rules in Frequent Pattern Mining

2018 ◽  
pp. 300-305
Keyword(s):  
Information Sharing ◽  
Pattern Mining ◽  
Data Distribution ◽  
Frequent Pattern Mining ◽  
Frequent Pattern ◽  
General Development ◽  
Secure Information ◽  
Evaluation Parameters ◽  
Secure Information Sharing

Information sharing among the associations is a general development in a couple of zones like business headway and exhibiting. As bit of the touchy principles that ought to be kept private may be uncovered and such disclosure of delicate examples may impacts the advantages of the association that have the data. Subsequently the standards which are delicate must be secured before sharing the data. In this paper to give secure information sharing delicate guidelines are bothered first which was found by incessant example tree. Here touchy arrangement of principles are bothered by substitution. This kind of substitution diminishes the hazard and increment the utility of the dataset when contrasted with different techniques. Examination is done on certifiable dataset. Results shows that proposed work is better as appear differently in relation to various past strategies on the introduce of evaluation parameters.

Sign in / Sign up

Export Citation Format

Share Document