TEMA

Text Mining and Applications

The track of Text Mining and Applications is a forum for researchers working in natural language processing (NLP), computational linguistics (CL), Machine Learning (ML) and related areas. Pure symbolic methods for Language Processing alone are unable to address human languages complexity. Text Mining and Machine Learning techniques applied to text, raw or annotated, brought up new insights and completely shifted the approaches to Human Language Technologies. Both approaches, symbolic and statistical based, when duly integrated, bridge the gap between language theories and effective use of languages, and enable important applications. Our aim, with this workshop, is to bring together innovative contributions to fill in this gap.

Topics of Interest

Text Mining:

• Language Models.
• Multi-word Units.
• Lexical Knowledge Acquisition.
• Word and Multi-word Sense Disambiguation.
• Semantic Restrictions Extraction.
• Acquisition and Usage of Ontologies in Text Mining.
• Pattern Extraction methodologies.
• Topic Segmentation.
• Word and Multi-word Translation Extraction.
• Sentiment Analysis.
• Text Entailment.
• Document Clustering and Classification.
• Algorithms and Data Structures for Text Mining.
• Information Extraction.

Applications:

• Natural Language Processing.
• Example-Based/Statistical Machine Translation.
• Automatic Summarization.
• Intelligent Information Retrieval.
• Multilingual access to multilingual information.
• Question-Answering Systems.
• E-training and E-learning.

Organising Committee

• Joaquim Francisco Ferreira da Silva, Universidade Nova de Lisboa, Portugal.
• José Gabriel Pereira Lopes, Universidade Nova de Lisboa, Portugal
• Gaël Dias, Universidade da Beira Interior, Portugal.
• Vitor Jorge Ramos Rocio, Universidade Aberta, Portugal

Contact Person

Joaquim Francisco Ferreira da Silva, jfs[at]di[.]fct[.]unl[.]pt