scholarly journals From text mining to knowledge mining: An integrated framework of concept extraction and categorization for domain ontology

2015 ◽  
Author(s):  
Saira Gillani Andleeb
Keyword(s):  
Text Mining ◽  
Domain Ontology ◽  
Knowledge Mining ◽  
Integrated Framework ◽  
Concept Extraction

A Methodical Text Mining on a Rationale of Domain Ontology

2019 ◽  
Author(s):  
Bhavan Kumar B ◽  
Vishal B L S R K ◽  
Bhargav K.R. ◽  
Revanth V ◽  
Chintakani Sai Gireesh
Keyword(s):  
Text Mining ◽  
Domain Ontology

Text Mining: Techniques, Applications, and Challenges

2018 ◽  
Vol 26 (04) ◽  
pp. 553-582 ◽  
Author(s):  
C. Justicia de la Torre ◽  
D. Sánchez ◽  
I. Blanco ◽  
M. J. Martín-Bautista
Keyword(s):  
Data Mining ◽  
Text Mining ◽  
Fuzzy Sets ◽  
Mining Area ◽  
Text Data ◽  
Text Data Mining ◽  
Knowledge Mining ◽  
Future Challenges

This work presents an overview of the text mining area, considering the most common techniques, and including proposals based on the application of fuzzy sets. Besides, some of the most frequent text mining applications are mentioned. We discuss the existing approaches, which we call text data mining, in relation to the recently proposed paradigm of text knowledge mining, and we conclude that both are different and complementary, in the sense that they are able to extract different knowledge pieces from text by using different reasoning mechanisms. Future challenges related to text knowledge mining are also briefly outlined.

Evaluating the Construction of Domain Ontologies for Recommender Systems Based on Texts

2011 ◽  
pp. 145-158
Author(s):  
Stanley Loh ◽  
Daniel Lichtnow ◽  
Thyago Borges ◽  
Gustavo Piltcher
Keyword(s):  
Text Mining ◽  
Supervised Learning ◽  
Recommender Systems ◽  
Digital Library ◽  
Recommender System ◽  
Software Tools ◽  
Domain Ontology ◽  
Engineering Process ◽  
Electronic Documents ◽  
Domain Experts

This chapter investigates different aspects in the construction of a domain ontology to a content-based recommender system. The recommender systems suggests textual electronic documents from a Digital Library, based on documents read by the users and based on textual messages posted in electronic discussions through a web chat. The domain ontology is used to represent the user’s interest and the content of the documents. In this context, the ontology is composed by a hierarchy of concepts and keywords. Each concept has a vector of keywords with weights associated. Keywords are used to identify the content of the texts (documents and messages), through the application of text mining techniques. The chapter discusses different approaches for constructing the domain ontology, including the use of text mining software tools for supervised learning, the interference of domain experts in the engineering process and the use of a normalization step.

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