Abstract
For any domain, understanding current trends is a challenging and attractive text mining task, especially when suitable tools are recursively applied to publications from the very domain they come from. Our research began by gathering a large corpus of Natural Language Processing (NLP) conferences and journals for both text and speech, covering documents produced from the 60's up to 2015. Our intent is to defy the old adage: The cobbler's children go unshod, so we developed a set of tools based on natural language technology to mine our scientific publication database and provide various interpretations according to a wide range of perspectives, including sub-domains, communities, chronology, terminology, conceptual evolution, re-use, trend prediction, and novelty detection.
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