AMC (Chen and Liu, KDD 2014)

AMC is an open-source Java package implementing the algorithm proposed in the paper (Chen and Liu, KDD 2014), created by Zhiyuan (Brett) Chen. For more details, please refer to this paper.

If you use this package, please cite the paper: Zhiyuan Chen and Bing Liu. Mining Topics in Documents: Standing on the Shoulders of Big Data. In Proceedings of KDD 2014, pages 1116-1125.

If you have any question or bug report, please send it to Zhiyuan (Brett) Chen ([email protected]).

Table of Contents

• Quick Start
• Commandline Arguments
• Input and Output
• Efficiency
• Contact Information

If you get the exception Java.Lang.OutOfMemoryError, please increase the Java heap memory for Eclipse: http://www.mkyong.com/eclipse/eclipse-java-lang-outofmemoryerror-java-heap-space/.

2. Use Maven

a. Then, change the current working directory to Src.

cd AMC/Src

b. Build the package.

mvn clean package

c. Increase the Java heap memory for Maven.

export MAVEN_OPTS=-Xmx1024m

d. Run the program.

mvn exec:java -Dexec.mainClass="launch.MainEntry"

Output

The output directory contains topic model results for LDA and AMC.

Under each model (LDA or AMC) directory, we have results for different datasets (small or big). Under the sub-folder "DomainModels", there are a list of domain folders where each domain folder contains topic model results for each domain. Under each domain folder, there are 9 files (can be opened by text editors):

1. domain.docs: each line (representing a document) contains a list of word ids.
2. domain.dtopicdist: document-topic distribution.
3. domain.knowl_cannotlinks: record the cannot-links used in the model (for AMC only).
4. domain.knowl_mustlinks: record the must-links used in the model (for AMC only).
5. domain.param: parameter settings.
6. domain.tassign: topic assignment for each word in each document.
7. domain.twdist: topic-word distribution
8. domain.twords: top words under each topic. The columns are separated by '\t' where each column corresponds to each topic.
9. domain.vocab: mapping from word id (starting from 0) to word.