Knowledge based dimensionality reduction for technical text mining

2014 ◽  
Author(s):  
Walid Shalaby ◽  
Wlodek Zadrozny ◽  
Sean Gallagher
Keyword(s):  
Text Mining ◽  
Dimensionality Reduction ◽  
Knowledge Based

scholarly journals Knowledge based word-concept model estimation and refinement for biomedical text mining

2015 ◽  
Vol 53 ◽  
pp. 300-307 ◽  
Author(s):  
Antonio Jimeno Yepes ◽  
Rafael Berlanga
Keyword(s):  
Text Mining ◽  
Biomedical Text ◽  
Biomedical Text Mining ◽  
Model Estimation ◽  
Concept Model ◽  
Knowledge Based

Efficiency Considerations for Vertical kNN Text Categorisation

2006 ◽  
Vol 05 (03) ◽  
pp. 211-222
Author(s):  
Imad Rahal ◽  
Hassan Najadat ◽  
William Perrizo
Keyword(s):  
Text Mining ◽  
Dimensionality Reduction ◽  
Text Classification ◽  
Subject Matter ◽  
Class Label ◽  
Time Efficiency ◽  
Text Databases ◽  
Nearest Neighbours ◽  
Class Labels ◽  
High Degree

The importance of text mining stems from the availability of huge volumes of text databases holding a wealth of valuable information that needs to be mined. Text mining is a coarse area encompassing many finer branches one of which is text categorisation or text classification. Text categorisation is the process of assigning class labels to documents based entirely on their textual contents where we are given a document d, and asked to find its subject matter or class label, Ci. In this paper, an optimised k-Nearest Neighbours classifier that uses discretisation, the P-tree technology, and dimensionality reduction to achieve a high degree of accuracy, space utilisation and time efficiency is proposed. One of the fundamental contributions of this work is that as new samples arrive, the proposed classifier can find the k nearest neighbours to the new sample from the training space without a single database scan.

Text Mining and Data Mining in Knowledge Organization and Discovery: The Making of Knowledge-Based Products

2003 ◽  
Vol 37 (1-2) ◽  
pp. 97-113 ◽  
Author(s):  
L. J. Haravu ◽  
A. Neelameghan
Keyword(s):  
Data Mining ◽  
Text Mining ◽  
Knowledge Organization ◽  
Knowledge Based

Knowledge-based Production Documentation Analysis: An Integrated Text Mining Architecture

2018 ◽  
Author(s):  
Johannes Zenkert ◽  
Christian Weber ◽  
Andre Klahold ◽  
Madjid Fathi ◽  
Kai Hahn
Keyword(s):  
Text Mining ◽  
Knowledge Based

scholarly journals A Survey of Text Matching Techniques

2021 ◽  
Vol 11 (1) ◽  
pp. 6656-6661
Author(s):  
A. Alqahtani ◽  
H. Alhakami ◽  
T. Alsubait ◽  
A. Baz
Keyword(s):  
Text Mining ◽  
Language Processing ◽  
Similarity Measures ◽  
Pattern Generation ◽  
Practical Applications ◽  
Knowledge Based ◽  
Vital Component ◽  
New Research ◽  
Matching Techniques ◽  
Text Matching

Text matching is the process of identifying and locating particular text matches in raw data. Text matching is a vital component in practical applications and an essential process in several fields. Furthermore, several dynamic techniques have been introduced in this context in order to create ease in pattern generation from words. The process involves matching of text files, text mining, text clustering, association rule extraction, world cloud, natural language processing, and text similarity measures (knowledge-based, corpus-based, string-based, and hybrid similarities). The string-based approach forms the most conspicuous form of text mining applied in different cases. The survey attempted in the present study covers a new research premise that uses text-matching to solve problems. The study also summarizes different approaches that are being used in this domain.

scholarly journals Improving Knowledge-Based Systems with statistical techniques, text mining, and neural networks for non-technical loss detection

2014 ◽  
Vol 71 ◽  
pp. 376-388 ◽  
Author(s):  
Juan I. Guerrero ◽  
Carlos León ◽  
Iñigo Monedero ◽  
Félix Biscarri ◽  
Jesús Biscarri
Keyword(s):  
Neural Networks ◽  
Text Mining ◽  
Statistical Techniques ◽  
Knowledge Based Systems ◽  
Knowledge Based

scholarly journals A method for extracting design rationale knowledge based on Text Mining

2017 ◽  
Vol 139 ◽  
pp. 00015
Author(s):  
Jihong Liu ◽  
Jiaji Wang ◽  
Kejian Wang
Keyword(s):  
Text Mining ◽  
Design Rationale ◽  
Knowledge Based
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