Automatic information retrieval through text-mining

• Author(s): Viana, Hugo Henrique Amorim
• Date: 2013
• Persistent ID: http://hdl.handle.net/10362/11308
• Origin: Repositório Institucional da UNL
• Subject(s): Text-mining; Stemmer; Clustering; Lucene
• Document Type: Master thesis
• Language: English
• Advisor(s): Barata, José
• Contributor(s): RUN

Description

The dissertation presented for obtaining the Master’s Degree in Electrical Engineering and Computer Science, at Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Nowadays, around a huge amount of firms in the European Union catalogued as Small and Medium Enterprises (SMEs), employ almost a great portion of the active workforce in Europe. Nonetheless, SMEs cannot afford implementing neither methods nor tools to systematically adapt innovation as a part of their business process. Innovation is the engine to be competitive in the globalized environment, especially in the current socio-economic situation. This thesis provides a platform that when integrated with ExtremeFactories(EF) project, aids SMEs to become more competitive by means of monitoring schedule functionality. In this thesis a text-mining platform that possesses the ability to schedule a gathering information through keywords is presented. In order to develop the platform, several choices concerning the implementation have been made, in the sense that one of them requires particular emphasis is the framework, Apache Lucene Core 2 by supplying an efficient text-mining tool and it is highly used for the purpose of the thesis.