Paper Info
Title
PicAChoo: a tool for customizable feature extraction utilizing characteristics of textual data
Abstract
Although documents have hundreds of thousands of unique words, only a small number of words are significantly useful for intelligent services. For this reason, feature extraction has become an important issue to be addressed in various fields, such as information retrieval, text mining, pattern recognition, etc. Numerous supporting tools for feature extraction are available, but most of them deal with text as a simple literal. Unfortunately, text is not just a literal, but a semantically significant unit including linguistic characteristics. So, we need customized extraction methods that consider the characteristics of source documents. PicAChoo stands for 'Pick And Choose', and it provides an environment which enables feature extraction methods using the structure of sentences and the part-of-speech information of words. Moreover, we suggest dynamic composition of different extraction methods without hard-coding.
Year
DOI
Venue
2009
10.1145/1516241.1516356
ICUIMC
Keywords
Field
DocType
important issue,extraction method,different extraction method,feature extraction,textual data,information retrieval,numerous supporting tool,text mining,customizable feature extraction,feature extraction method,dynamic composition,part-of-speech information,pattern recognition,part of speech
Text mining,Information retrieval,Feature (computer vision),Computer science,Feature extraction,Source document,Relationship extraction
Conference
Citations 
PageRank 
References 
3
0.41
8
Authors
3
Name
Order
Citations
PageRank
Jaeseok Myung1816.48
Jung-Yeon Yang2152.03
Sang-goo Lee3832151.04