v1.0.1

README.md

@@ -7,17 +7,18 @@ learning and data mining literature, and to introduce **new datasets**
 of different dimensionalities, sizes, and cluster types.
 
 This repository is part of the
-[Framework for Benchmarking Clustering Algorithms](https://clustering-benchmarks.gagolewski.com).
+[**Framework for Benchmarking Clustering Algorithms**](https://clustering-benchmarks.gagolewski.com).
 It hosts the datasets from version 1 of the benchmark suite.
 
 Refer to <https://clustering-benchmarks.gagolewski.com>
-for a detailed description, file format specification, and literature
-references.
+for a detailed description, file format specification,
+example Python/R/MATLAB code, datasets explorer,
+and literature references.
 
 
 
 **Editor/Maintainer**:
-[Marek Gagolewski](https://www.gagolewski.com)
+[Marek Gagolewski](https://www.gagolewski.com).
 
 
 **How to Cite**: Please cite the following paper which describes
@@ -77,7 +78,6 @@ downloadable snapshots.
     Genie: A new, fast, and outlier-resistant hierarchical
     clustering algorithm, *Information Sciences* **363**, 2016, pp. 8–23,
     DOI: [10.1016/j.ins.2016.05.003](https://doi.org/10.1016/j.ins.2016.05.003).
-
     The datasets have been archived at
     <https://github.com/gagolews/clustering-data-v0>.
 
@@ -87,9 +87,5 @@ downloadable snapshots.
 <https://clustering-benchmarks.gagolewski.com> gives the description
 of our framework for benchmarking clustering algorithms.
 
-Raw results generated by many clustering methods when run on the datasets from
-this repository can be found at
-<https://github.com/gagolews/clustering-results-v1/>.
-
-See <https://genieclust.gagolewski.com>
-for an example study featuring this benchmark suite.
+It also mentions where to find raw and aggregated results generated
+by many clustering methods when run on the datasets from this repository.