This is a mirror from the repository located on Illimine here. This only contains the matlab source files; it does not contain the data. The link on Illimine contains the data.
**** Illimine Copyright ****
University of Illinois at Urbana-Champaign, 2015
illimine.cs.illinois.edu
Additional Copyright
This package contains the source code and the dataset used in the following paper:
Chi Wang, Xueqing Liu, Yanglei Song, Jiawei Han. Scalable Moment-based Inference for Latent Dirichlet Allocation. ECMLPKDD, 2014.
If you use any contents in this package, please cite:
@inproceedings{wang14, title={Scalable Moment-based Inference for Latent Dirichlet Allocation}, author={Wang, Chi and Liu, Xueqing and Song, Yanglei and Han, Jiawei}, booktitle={ECMLPKDD}, pages={290-305}, year={2014}, }
Code explanation
(1). Input is in folder /Data. It contains two files: Data/test.corpus, which is document-word file (each line is in the format 'docID wordID') and Data/test.dict, which is vocabulary file (each line is in the format 'word')
(2). Output is in folder /Data. It contains two file:
a) Data/test.stod.mat. It contains 3 parts:
-- 1. alpha0, which is the summation of Dirichlet priors
-- 2. alpha, which is the inferred Dirichlet prior of each topic
-- 3. twmat, which is a k (number of topics) x V (vocabulary size) matrix,
the i-th row being the i-th inferred topic distribution p(w|topic=i)
b) Data/test.topic.mat. It contains 1 part, a k x 1 cell, the i-th cell
being the topic representation of the i-th topic (which is the top 10
words ordered by p(w|topic=i))
Data explanation
Data/csabstract contains CS abstracts used in the paper.
For AP news dataset, please visit http://trec.nist.gov/data/docs_eng.html.
**** For More Questions ****
Please contact illimine.cs.illinois.edu or Chi Wang ([email protected])