MINING FOR RELEVANT TERMS FROM LOG FILES

被引:0
|
作者
Saneifar, Hassan [1 ,2 ]
Bonniol, Stephane [2 ]
Laurent, Anne [1 ]
Poncelet, Pascal [1 ]
Roche, Mathieu [1 ]
机构
[1] Univ Montpellier 2, CNRS, LIRMM, 161 Rue Ada, F-34392 Montpellier 5, France
[2] Sain IP Technol, F-34960 Montpellier, France
关键词
Natural language processing; Information retrieval; Terminology extraction; Terminology ranking; Log files;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Information extracted from log files of computing systems can be considered one of the important resources of information systems. In the case of Integrated Circuit design, log files generated by design tools are not exhaustively exploited. The logs of this domain are multi-source, multi-format, and have a heterogeneous and evolving structure. Moreover, they usually do not respect the grammar and the structures of natural language though they are written in English. According to features of such textual data, applying the classical methods of information extraction is not an easy task, more particularly for terminology extraction. We have previously introduced EXTERLOG approach to extract the terminology from such log files. In this paper, we introduce a new developed version of EXTERLOG guided by Web. We score the extracted terms by a Web and context based measure. We favor the more relevant terms of domain and emphasize the precision by filtering terms based on their scores. The experiments show that EXTERLOG is well-adapted terminology extraction approach from log files.
引用
收藏
页码:77 / +
页数:2
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