A Comprehensive Evaluation of a Novel Approach to Probabilistic Information Extraction from Large Unstructured Datasets

被引：0
|
作者：
Trovati, Marcello [1 ]
机构：
[1] Univ Derby, Dept Comp & Math, Derby DE22 1GB, England
来源：
2015 International Conference on Intelligent Networking and Collaborative Systems IEEE INCoS 2015 | 2015年
关键词：
Knowledge discovery; Information extraction; Data analytics;
D O I：
10.1109/INCoS.2015.36
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we discuss the evaluation of the probabilistic extraction as introduced in [1], by considering three different datasets introduced in [1]-[3]. the results show the potential of the approach, as well as its reliability and efficiency when analyzing datasets with different properties and structures. This is part of ongoing research aiming to provide a tool to extract, assess and visualize intelligence extracted from large unstructured datasets.
引用
收藏
页码：459 / 462
页数：4
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