NCBITextLib is a simple but effective software library that allows one to build and access an infrastructure for large-scale text mining tasks. This library only provides basic C++ classes for building various text mining tools. Since the library provides a simple to use interface for connecting an internal text data structure to other high-level applications, it is straightforward to build ML software upon NCBITextLib. Currently, we provide three machine learning classes (naive Bayes, support vector machine and theme analysis algorithms) and example codes that use NCBITextLib.
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- g++ (gcc) 4.8.1
- OS: CentOS release 6.7
- Download
- Building a library
- cd ./lib
- make
- Compiling example programs
- cd ./applications
- make [file name], e.g. make make_db
- Machine learing classes and examples
- cd ./applications
- BayeX.h: naive Bayes classifier (inherit from CMark)
- HubeX.h: support vector machine classifier (inherit from CMark)
- ThemX.h: theme analysis algorithm (inherit from BayeX)
- make_doc: create a Doc from samples.txt
- make_xpost: create a XPost from a Doc set (should run make_doc and make_xpost beforhand for other applications)
- run_BayeX: naive Bayes classifier example
- run_HubeX: support vector machine classifier example
- run_ThemX: theme analysis algorithm example
- find_neighbors: find neighboring documents from a seed document
NOTE: sample programs use XPost, thus should run make_doc and make_xpost beforehand.
- Sun Kim
- W. John Wilbur
- Won Kim
- Donald C. Comeau
- Zhiyong Lu
Please contact sun.kim@nih.gov if you have any questions or comments.