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Natural Language Processing Technologies for Document Profiling

Antonio Guillén, Yoan Gutiérrez, Rafael Muñoz


Abstract
Nowadays, search for documents on the Internet is becoming increasingly difficult. The reason is the amount of content published by users (articles, comments, blogs, reviews). How to facilitate that the users can find their required documents? What would be necessary to provide useful document meta-data for supporting search engines? In this article, we present a study of some Natural Language Processing (NLP) technologies that can be useful for facilitating the proper identification of documents according to the user needs. For this purpose, it is designed a document profile that will be able to represent semantic meta-data extracted from documents by using NLP technologies. The research is basically focused on the study of different NLP technologies in order to support the creation our novel document profile proposal from semantic perspectives.
Anthology ID:
R17-1039
Volume:
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017
Month:
September
Year:
2017
Address:
Varna, Bulgaria
Editors:
Ruslan Mitkov, Galia Angelova
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
284–290
Language:
URL:
https://doi.org/10.26615/978-954-452-049-6_039
DOI:
10.26615/978-954-452-049-6_039
Bibkey:
Cite (ACL):
Antonio Guillén, Yoan Gutiérrez, and Rafael Muñoz. 2017. Natural Language Processing Technologies for Document Profiling. In Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017, pages 284–290, Varna, Bulgaria. INCOMA Ltd..
Cite (Informal):
Natural Language Processing Technologies for Document Profiling (Guillén et al., RANLP 2017)
Copy Citation:
PDF:
https://doi.org/10.26615/978-954-452-049-6_039