TEMA – Text Mining and Applications

Human languages are complex by nature and efforts in pure symbolic approaches alone have been unable to provide fully satisfying results. Text Mining and Machine Learning techniques applied to texts, raw or annotated, brought up new insights and completely shifted the approaches to Human Language Technologies. Both approaches, symbolic and statistically based, when duly integrated, have shown capabilities to bridge the gap between language theories and effective use of languages, and can enable important applications in real-world heterogeneous environment such as the Web.
The 4th Track of Text Mining and Applications (TeMA 2013) is a forum for researchers working in Human Language
Technologies i.e. Natural Language Processing (NLP), Computational Linguistics (CL), Natural Language Engineering (NLE), Text Mining (TM) and related areas. Authors are invited to submit their papers on any of the issues identified below. Papers will be blindly reviewed by three members of the Program Committee. Best papers will be published at Springer, in LNAI series. If there are additional papers whose quality is sufficiently high for deserving to be presented at TeMA’13, those other accepted papers will be published in a conference proceedings book.

Topics of Interest

Topics include but are not limited to:

Text Mining:

– Multi-word Units
– Lexical Knowledge Acquisition
– Word and Multi-word Sense Disambiguation.
– Sentiment Analysis
– Text Mining Models for Social Network Analysis
– Acquisition and Usage of Ontologies
– Topic Segmentation
– Extraction of Translation Equivalents
– Word and Multi-word Translation Extraction
– Text Entailment
– Document Clustering and Classification
– Algorithms and Data Structures for Text Mining
– Information Extraction


– Natural Language Processing
– Machine Translation
– Automatic Summarization
– Intelligent Information Retrieval
– Cross-language access to multilingual information
– E-training, E-learning and Question-Answering Systems
– Web Mining


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