Please use this identifier to cite or link to this item:
https://hdl.handle.net/10216/78873| Author(s): | Carla Abreu teixeira, j Eugénio Oliveira |
| Title: | ENCADEAr: encadeamento automático de notícias |
| Issue Date: | 2015 |
| Abstract: | This work aims at defining and evaluating different techniques to automa- tically build temporal news sequences. The approach proposed is composed by three steps: (i) near duplicate documents detention; (ii) keywords ex- traction; (iii) news sequences creation. This approach is based on: Natural Language Processing, Information Extraction, Name Entity Recognition and supervised learning algorithms. The proposed methodology got a precision of 93.1% for news chains sequences creation. |
| Description: | This work aims at defining and evaluating different techniques to automa- tically build temporal news sequences. The approach proposed is composed by three steps: (i) near duplicate documents detention; (ii) keywords ex- traction; (iii) news sequences creation. This approach is based on: Natural Language Processing, Information Extraction, Name Entity Recognition and supervised learning algorithms. The proposed methodology got a precision of 93.1% for news chains sequences creation. |
| Subject: | Informática, Ciências da computação e da informação Informatics, Computer and information sciences |
| Scientific areas: | Ciências exactas e naturais::Ciências da computação e da informação Natural sciences::Computer and information sciences |
| URI: | https://hdl.handle.net/10216/78873 |
| Document Type: | Artigo em Revista Científica Internacional |
| Rights: | openAccess |
| License: | https://creativecommons.org/licenses/by-nc/4.0/ |
| Appears in Collections: | FEUP - Artigo em Revista Científica Internacional |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 101813.pdf | artigo em revista | 974.87 kB | Adobe PDF |  View/Open |
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