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Information Filtering and Retrieval - DART
Chairs: Cristian Lai, Alessandro Giuliani and Giovanni Semeraro
DART 2015 intends to provide a more interactive and focused platform for researchers and practitioners for presenting and discussing new and emerging ideas. It is focused on researching and studying new challenges in intelligent information filtering and retrieval. In particular, DART aims to investigate novel systems and tools to web scenarios and semantic computing. In so doing, DART will contribute to discuss and compare suitable novel solutions based on intelligent techniques and applied in real-world applications.
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Text Mining - SSTM
Chair: Ana Fred
With the increasing popularity and availability of Internet-based technologies, as well as the proliferation of digital computing devices and their use in communication, huge amounts of Human generated content is produced every day in the form of documents, email, instant messaging, social network sites, blogs, and other textual corpora. As a result, we have witnessed an increased demand for systems and algorithms capable of mining textual data, seeking interesting characteristics, hidden patterns, structure, trends, knowledge and key relationships within these large textual corpora. Text mining, combining the disciplines of data mining, information extraction, information retrieval, text categorization, probabilistic modeling, linear algebra, machine learning, and computational linguistics, is a new interdisciplinary field that emerged to address these issues. Examples of emergent applications include metadata generation, visualization techniques, information extraction, text segmentation and classification, text summarization, and trend analysis, to name a few.
This special session aims at sharing new ideas and works on models and approaches for improving over state of the art techniques for mining unstructured, semi-structured, and fully structured textual data.
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