feature description

README.md

@@ -2,7 +2,18 @@
 
 [![Build Status](https://travis-ci.org/jaak-s/BayesianDataFusion.jl.svg?branch=master)](https://travis-ci.org/jaak-s/BayesianDataFusion.jl)
 
-Implementation of data fusion methods in Julia, specifically **Macau**, **BPMF**.
+Implementation of data fusion methods in Julia, specifically **Macau**, **BPMF** (Bayesian Probabilistic Matrix Factorization). Supported features:
+* Factorization of matrices (without or with side information)
+* Factorization of tensors (without or with side information)
+* Co-factorization of multiple matrices and tensors (any side information is
+  possible)
+* Side information inside relation
+* Parallelization (multi-core and multi-node)
+
+BayesianDataFusion uses Gibbs sampling to learn the latent vectors and link
+matrices. In addition to predictions Gibbs sampling also provides estimates
+of **standard deviation** and possible other metrics (that can be computed from
+samples).
 
 ## Installation
 ```julia