Pradipto Das - SUNY Buffalo, CSE Dept. Research Softwares

p r e v

Links to Softwares

The AToM Framework

I have started working on the AToM (Another Topic Model) framework that implements a framework for statistical topic modeling codes in C++. [ Gibbs-LDA download]

Note: Due to lack of time and other commitments, this version implements a basic Gibbs sampler type LDA (Latent Dirichlet Allocation) only. The softwares here are intended as quick and dirty prototypes for students. Some additional comments:

The code uses the IP (Imputation-Posterior) iterative framework for sampling.
The goal was to have an interpretive version of Hal Daume's HBC just like Java vs. C++. HBC is really good but often times, the genarated code becomes very hard to follow for the uninitiated.
I am not sure I will ever get to completing a full topic model interpreter any time soon. Feel free to try it out and extend it any way you like.

This is the Variational Bayesian version of LDA (David Blei's LDA) written in C++. The code is written using the EM (Expectation Maximization) framework that can be integrated with AToM with some effort (can be used as a standalone module for now)

Prototypes - requires polishing

Tag-Topic Model Codes

Some C++ prototype codes from our 2011 CIKM paper - "Simultaneous Joint and Conditional Modeling of Documents Tagged from Two Perspectives"
- Download TagLDA in C++
- Download MMLDA in C++
- Download CorrMMLDA in C++
- Download METag²LDA in C++
- Download CorrMETag²LDA in C++
The model names may be different in code than those in the paper. Will do some refactoring if time permits.

Some Topic Model Codes from Earlier Times

- Download Variational Bayesian LDA in C++

Readme.txt

- Download Gibbs sampling base LDA in C++

Readme.txt

Notes on Topic Model Codes

NOTE: All ids for documents and observed data (terms, document level tags and word level tags) start from 0 and are sequential with an increment of 1.
The comments in the source files can be misleading due copy-pasting. These will be fixed as time permits.

TA Corner

TA1. Adhoc Datastructures

[ This Eclipse CDT project] serves as a repository for standard algorithms that are not found in the standard C++ stl (except heaps). Source codes have been borrowed from several sources. Being written entirely in C++, this package currently includes implementation for Multi-Way-Merge or K-Way-Merge, B+ Tree, a minimal Trie, Heaps using vectors and a minimal on-disk binary search (often used for inverted index searching based on query words). WishList: include code from Google's sparse hash, SGI STL hash_map and TPIE See the readme file inside the tarball for compilation instructions. The SGI STL hash_map can be accessed using standard c++ library in most nix systems and can be used in code as:

#include<ext/hash_map>
using namespace __gnu_cxx;

TA2. CSE 4/535 IR course - Fall 2010

[ Warmup code] This is an adhoc implementatation for the first project. The expected behavior of this code is to extract internal wiki links from wiki markups. For more info on how the markup files look like, please see the files under the "Wiki" subdirectory under the data directory.
(+) First project.
(+) Second project.
(+) Third project.

TA3. CSE 4/535 IR course - Fall 2009

[ Warmup notes on C++ STL] The content in this pdf was geared towards use in first project. The focus of the project was on document language identification using character bi-grams. Stl bitset was used for unicode extraction. Format for unicode is well described in the UTF-8 article in Wikipedia
(*) Find the UTF-8 code chart here

n e x t

Please report bugs to me. My email can be found at the bottom right corner of this page with "university domain" being substituted with "buffalo . edu". Thanks!

email: pdas3 at [university domain]