Mining of graphics for information and knowledge retrieval

被引：8
|
作者：
Avramenko, Yuri [1 ]
Ani, Elisabeta-Cristina [1 ,2 ]
Kraslawski, Andrzej [1 ]
Agachi, Paul Serban [2 ]
机构：
[1] Lappeenranta Univ Technol, Dept Chem Technol, FIN-53851 Lappeenranta, Finland
[2] Univ Babes Bolyai, Fac Chem & Chem Engn, Cluj Napoca 400028, Romania
来源：
COMPUTERS & CHEMICAL ENGINEERING | 2009年 / 33卷 / 03期
关键词：
Information retrieval; Case-based reasoning; Diffusion calculation; LONGITUDINAL DISPERSION COEFFICIENT; CHANNELS; STREAMS;
D O I：
10.1016/j.compchemeng.2008.10.023
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The oversupply of data, information and knowledge, even after preliminary keywords and topics search, is a well-known problem in R&D activities. One of the approaches aimed at limiting the negative impact of the surplus of information is its automated intelligent preprocessing and reuse. The paper describes a method for identification of the concepts which is based on combination of subject-driven document clustering, shape analysis, trends understanding and relevant context retrieval via semantic analysis. The goal is to extract potentially interesting knowledge from a set of documents based on analysis of graphical information and next to explain the mechanism of the studied process. The proposed method is implemented in the software suite which contains source searching tool, plot comparator and semantic analyzer. The method has been applied to identify the calculation process, using channel geometry characteristics, of the longitudinal dispersion coefficients for one branch of the Somes river in Romania. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码：618 / 627
页数：10
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