A Distributed Information Extraction System Integrating Ontological Knowledge and Probabilistic Classifiers

被引：1

作者：

Alicante, Anita ^{[1
]}

Benerecetti, Massimo ^{[1
]}

Corazza, Anna ^{[1
]}

Silvestri, Stefano ^{[1
]}

机构：

[1] Univ Napoli Federico II, Dept Elect Engn & Informat Technol, Via Claudio 21, I-80125 Naples, Italy

来源：

2014 NINTH INTERNATIONAL CONFERENCE ON P2P, PARALLEL, GRID, CLOUD AND INTERNET COMPUTING (3PGCIC) | 2014年

关键词：

Information Extraction; Markov Random Fields; Distributed Approach;

D O I：

10.1109/3PGCIC.2014.87

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this work we consider the problem of extracting concepts and relations between them from documents, aiming at constructing an index for a more semantically oriented search engine. While assessment is performed on a biomedical application, the proposed solutions can be also applied to different domains. With the distributed architecture proposed, we obtain an approach that can be applied also on large data sets. Experimental assessment has been performed on a standard data set, BioNLP 2013.

引用

页码：420 / 425

页数：6

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