Abstract
A controlled use of omnipresent data can leverage a potential of services never reached before. In this paper, we propose a user driven approach to take advantage of massive data streams. Our solution, named Stream2Text, relies on a personalized and continuous refinement of data to generate texts (in natural language) that provide a tailored synthesis of relevant data. It enables monitoring by a wide range of users as text streams can be shared on social networks or used individually on mobile devices.
Cite
CITATION STYLE
Labbé, C., Roncancio, C., & Bras, D. (2015). A personal storytelling about your favorite data. In ENLG 2015 - Proceedings of the 15th European Workshop on Natural Language Generation (pp. 166–174). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w15-4727
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