The Role of Domain Ontology in Text Mining Applications: The ADDMiner Project

2006 ◽  
Author(s):  
Ana B. Garcia ◽  
Inhauma Ferraz ◽  
Fernando Pinto
Keyword(s):  
Text Mining ◽  
Domain Ontology

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 for economic geographical sectoral analysis of the pulp and paper industry in European Russia

2021 ◽  
Vol 71 (1) ◽  
pp. 18-33
Author(s):  
I.F. Kuzminov ◽  
P.A. Lobanova
Keyword(s):  
Text Mining ◽  
Paper Industry ◽  
Pulp And Paper Industry ◽  
Spatial Development ◽  
Pulp And Paper ◽  
European Russia ◽  
Data Sources ◽  
Management Decisions ◽  
Timber Industry

The authors show the need and some existing opportunities for analysis of non-traditional data sources to obtain a complete and more relevant picture of industries spatial development. The research methodology includes the use of text mining for economic and geographical studies. The relevance of the research is determined by insufficient completeness of official statistical data, cheapening of relevant information processing technologies and abundance of large text data sources in open access. The article discusses the role of the pulp and paper industry (as a key part of the timber industry) in economic and spatial development of modern Russia. The authors identify main trends in the economic and spatial development of the pulp and paper industry of European Russia, draw the conclusions on the expected industry trends and give recommendations for strategic management decisions to respond to industry challenges. The authors claim that the industry needs liberalization and stabilization, primarily through moratoriums on policy changes. The role of the use of big data, and in particular of text mining in economic and geographical research for reasonable and objective conclusions formation that can be used to make timely and balanced management decisions in the timber industry and the pulp and paper industry, is emphasized.

Sentiment Analysis with Text Mining in Contexts of Big Data

2017 ◽  
Vol 13 (3) ◽  
pp. 47-67 ◽  
Author(s):  
Carina Sofia Andrade ◽  
Maribel Yasmina Santos
Keyword(s):  
Big Data ◽  
Text Mining ◽  
Sentiment Analysis ◽  
Decision Making Process ◽  
Practical Applications ◽  
Information Models ◽  
Evolution Of Technology ◽  
The Common ◽  
Analyse Data

The evolution of technology, along with the common use of different devices connected to the Internet, provides a vast growth in the volume and variety of data that are daily generated at high velocity, phenomenon commonly denominated as Big Data. Related with this, several Text Mining techniques make possible the extraction of useful insights from that data, benefiting the decision-making process across multiple areas, using the information, models, patterns or tendencies that these techniques are able to identify. With Sentiment Analysis, it is possible to understand which sentiments and opinions are implicit in this data. This paper proposes an architecture for Sentiment Analysis that uses data from the Twitter, which is able to collect, store, process and analyse data on a real-time fashion. To demonstrate its utility, practical applications are developed using real world examples where Sentiment Analysis brings benefits when applied. With the presented demonstration case, it is possible to verify the role of each used technology and the techniques adopted for Sentiment Analysis.

An Ontological Approach to Managing Project Memories in Organizations

2011 ◽  
pp. 233-261 ◽  
Author(s):  
Davy Monticolo ◽  
Vincent Hilaire ◽  
Samuel Gomes ◽  
Abderrafiaa Koukam
Keyword(s):  
Mechanical Design ◽  
Domain Ontology ◽  
Organizational Memory ◽  
Knowledge Modeling ◽  
Distributed Knowledge ◽  
Agent Model ◽  
Professional Activities ◽  
Ontological Approach ◽  
Multi Agent

Knowledge Management (KM) is considered by many organizations a key aspect in sustaining competitive advantage. In the mechanical design domain, the KM facilitates the design of routine product and brings a saving time for innovation. This chapter describes the specification of a project memory as an organizational memory to specify knowledge to capitalize all along project in order to be reuse. Afterwards it presents the design of a domain ontology and a multi agent system to manage project memories all along professional activities. As a matter of fact, these activities require that engineers, with different specialities, collaborate to carry out the same goal. Inside professional activities; they use their knowhow and knowledge in order to achieve the laid down goals. The professional actors competences and knowledge modeling allows the design and the description of agents’ know-how. Furthermore, the paper describes the design of our agent model based on an organisational approach and the role of a domain ontology called OntoDesign to manage heterogeneous and distributed knowledge.

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