A Hybrid Approach for Learning Concept Hierarchy from Malay Text Using GAHC and Immune Network

2009 ◽  
pp. 315-328
Author(s):  
Mohd Zakree Ahmad Nazri ◽  
Siti Mariyam Shamsuddin ◽  
Azuraliza Abu Bakar ◽  
Salwani Abdullah
Keyword(s):  
Hybrid Approach ◽  
Immune Network ◽  
Concept Hierarchy ◽  
Learning Concept

A hybrid approach for learning concept hierarchy from Malay text using artificial immune network

2010 ◽  
Vol 10 (1) ◽  
pp. 275-304 ◽  
Author(s):  
Mohd Zakree Ahmad Nazri ◽  
Siti Mariyam Shamsuddin ◽  
Azuraliza Abu Bakar ◽  
Salwani Abdullah
Keyword(s):  
Hybrid Approach ◽  
Immune Network ◽  
Artificial Immune ◽  
Concept Hierarchy ◽  
Artificial Immune Network ◽  
Learning Concept

scholarly journals Formal context reduction in deriving concept hierarchies from corpora using adaptive evolutionary clustering algorithm star

2021 ◽  
Author(s):  
Bryar A. Hassan ◽  
Tarik A. Rashid ◽  
Seyedali Mirjalili
Keyword(s):  
Clustering Algorithm ◽  
Concept Lattice ◽  
Formal Context ◽  
Formal Concept ◽  
Context Analysis ◽  
Concept Hierarchy ◽  
Evolutionary Clustering ◽  
Learning Concept ◽  
Concept Hierarchies

AbstractIt is beneficial to automate the process of deriving concept hierarchies from corpora since a manual construction of concept hierarchies is typically a time-consuming and resource-intensive process. As such, the overall process of learning concept hierarchies from corpora encompasses a set of steps: parsing the text into sentences, splitting the sentences and then tokenising it. After the lemmatisation step, the pairs are extracted using formal context analysis (FCA). However, there might be some uninteresting and erroneous pairs in the formal context. Generating formal context may lead to a time-consuming process, so formal context size reduction is require to remove uninterested and erroneous pairs, taking less time to extract the concept lattice and concept hierarchies accordingly. In this premise, this study aims to propose two frameworks: (1) A framework to review the current process of deriving concept hierarchies from corpus utilising formal concept analysis (FCA); (2) A framework to decrease the formal context’s ambiguity of the first framework using an adaptive version of evolutionary clustering algorithm (ECA*). Experiments are conducted by applying 385 sample corpora from Wikipedia on the two frameworks to examine the reducing size of formal context, which leads to yield concept lattice and concept hierarchy. The resulting lattice of formal context is evaluated to the standard one using concept lattice-invariants. Accordingly, the homomorphic between the two lattices preserves the quality of resulting concept hierarchies by 89% in contrast to the basic ones, and the reduced concept lattice inherits the structural relation of the standard one. The adaptive ECA* is examined against its four counterpart baseline algorithms (Fuzzy K-means, JBOS approach, AddIntent algorithm, and FastAddExtent) to measure the execution time on random datasets with different densities (fill ratios). The results show that adaptive ECA* performs concept lattice faster than other mentioned competitive techniques in different fill ratios.

Learning Concept Hierarchy from Folksonomy

2011 ◽  
Author(s):  
Shubin Cai ◽  
Heng Sun ◽  
Sishan Gu ◽  
Zhong Ming
Keyword(s):  
Concept Hierarchy ◽  
Learning Concept

scholarly journals A hybrid approach for hot spot prediction and deep representation of hematological protein – drug interactions

2018 ◽  
Vol 7 (1.9) ◽  
pp. 145
Author(s):  
Bipin Nair B.J ◽  
Lijo Joy
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Learning Algorithm ◽  
Hot Spot ◽  
Research Work ◽  
Hybrid Approach ◽  
Prediction Algorithm ◽  
Protein Drug ◽  
Machine Learning Algorithm ◽  
Learning Concept

In our research work we will collect the data of drugs as well as protein regarding hematic diseases, then applying feature extraction as well as classification, predict hot spot and non-hot spot then we are predicting the hot region using prediction algorithm. Parallelly from the hematological drug we are extracting the feature using molecular finger print then classifying using a classifier and applying deep learning concept to reduce the dimensionality then finally using machine learning algorithm predicting which drug will interact with the help of a hybrid approach.

Surgical and endovascular hybrid approach in peripheral arterial disease of the lower limbs

VASA ◽  
2016 ◽  
Vol 45 (5) ◽  
pp. 417-422 ◽  
Author(s):  
Anouk Grandjean ◽  
Katia Iglesias ◽  
Céline Dubuis ◽  
Sébastien Déglise ◽  
Jean-Marc Corpataux ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Peripheral Arterial Disease ◽  
Limb Salvage ◽  
Hybrid Approach ◽  
Arterial Disease ◽  
Early Mortality ◽  
Secondary Patency ◽  
Limb Salvage Rate ◽  
Peripheral Arterial ◽  
Salvage Rate

Abstract. Background: Multilevel peripheral arterial disease is frequently observed in patients with intermittent claudication or critical limb ischemia. This report evaluates the efficacy of one-stage hybrid revascularization in patients with multilevel arterial peripheral disease. Patients and methods: A retrospective analysis of a prospective database included all consecutive patients treated by a hybrid approach for a multilevel arterial peripheral disease. The primary outcome was the patency rate at 6 months and 1 year. Secondary outcomes were early and midterm complication rate, limb salvage and mortality rate. Statistical analysis, including a Kaplan-Meier estimate and univariate and multivariate Cox regression analyses were carried out with the primary, primary assisted and secondary patency, comparing the impact of various risk factors in pre- and post-operative treatments. Results: 64 patients were included in the study, with a mean follow-up time of 428 days (range: 4 − 1140). The technical success rate was 100 %. The primary, primary assisted and secondary patency rates at 1 year were 39 %, 66 % and 81 %, respectively. The limb-salvage rate was 94 %. The early mortality rate was 3.1 %. Early and midterm complication rates were 15.4 % and 6.4 %, respectively. The early mortality rate was 3.1 %. Conclusions: The hybrid approach is a major alternative in the treatment of peripheral arterial disease in multilevel disease and comorbid patients, with low complication and mortality rates and a high limb-salvage rate.

Delayed Closure of Multiple Muscular Ventricular Septal Defects in an Infant after Coarctation Repair and a Hybrid Procedure�A Case Report

2011 ◽  
Vol 14 (1) ◽  
pp. 67 ◽  
Author(s):  
Ireneusz Haponiuk ◽  
Maciej Chojnicki ◽  
Radosaw Jaworski ◽  
Jacek Juciski ◽  
Mariusz Steffek ◽  
...  
Keyword(s):  
Septal Defect ◽  
Color Doppler ◽  
Hybrid Approach ◽  
Ventricular Septal Defects ◽  
Color Doppler Echocardiography ◽  
Septal Defects ◽  
Coarctation Repair ◽  
Step Procedure ◽  
The Right ◽  
Delayed Closure

There are several strategies of surgical approach for the repair of multiple muscular ventricular septal defects (mVSDs), but none leads to a fully predictable, satisfactory therapeutic outcome in infants. We followed a concept of treating multiple mVSDs consisting of a hybrid approach based on intraoperative perventricular implantation of occluding devices. In this report, we describe a 2-step procedure consisting of a final hybrid approach for multiple mVSDs in the infant following initial coarctation repair with pulmonary artery banding in the newborn. At 7 months, sternotomy and debanding were performed, the right ventricle was punctured under transesophageal echocardiographic guidance, and the 8-mm device was implanted into the septal defect. Color Doppler echocardiography results showed complete closure of all VSDs by 11 months after surgery, probably via a mechanism of a localized inflammatory response reaction, ventricular septum growth, and implant endothelization.

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