Update README.rst

README.rst

@@ -2,30 +2,44 @@
 DeepWalk
 ===============================
 
+DeepWalk uses short random walks to learn representations for vertices in graphs.
+
 Usage
 -----
-$deepwalk --help
-
-input:  adjacency list
-
-    1 2 3 4 5 6 7 8 9 11 12 13 14 18 20 22 32
 
-    2 1 3 4 8 14 18 20 22 31
+**Example Usage**
+    ``$deepwalk --input example_graphs/karate.adjlist --output karate.embeddings``
 
-    3 1 2 4 8 9 10 14 28 29 33
+**--input**:  *input_filename*
 
-    ...
+    1. ``--format adjlist`` for an adjacency list, e.g::
 
-output: representations in skipgram format - first line is header, all other lines are node-id and representation
-
-    34 64
+        1 2 3 4 5 6 7 8 9 11 12 13 14 18 20 22 32
+        2 1 3 4 8 14 18 20 22 31
+        3 1 2 4 8 9 10 14 28 29 33
+        ...
+    
+    2. ``--format edgelist`` for an edge list, e.g::
+    
+        1 2
+        1 3
+        1 4
+        ...
+    
+    3. ``--format mat`` for a Matlab MAT file containing an adjacency matrix
+        (note, you must also specify the variable name of the adjacency matrix ``--matfile-variable-name``)
 
-    1 0.016579 -0.033659 0.342167 -0.046998 ...
+**--output**: *output_filename*
 
-    2 -0.007003 0.265891 -0.351422 0.043923 ...
+    The output representations in skipgram format - first line is header, all other lines are node-id and *d* dimensional representation::
 
-    ...
+        34 64
+        1 0.016579 -0.033659 0.342167 -0.046998 ...
+        2 -0.007003 0.265891 -0.351422 0.043923 ...
+        ...
 
+**Full Command List**
+    The full list of command line options is available with ``$deepwalk --help``
 
 Requirements
 ------------
@@ -45,29 +59,26 @@ Installation
 
 Citing
 ------
-    @inproceedings{2014-perozzi-deepwalk,
-
-    author    = {Bryan Perozzi and Rami Al-Rfou and Steven Skiena},
-
-    title     = {DeepWalk: Online Learning of Social Representations},
-
-    booktitle = {Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
-
-    series = {KDD '14},
-
-    year = {2014},
-
-    month = {August},
-
-    location = {New York, NY, USA},
-
-    publisher = {ACM},
-    
-    address = {New York, NY, USA},
-    
+If you find DeepWalk useful in your research, we ask that you cite the following paper::
+
+    @inproceedings{Perozzi:2014:DOL:2623330.2623732,
+     author = {Perozzi, Bryan and Al-Rfou, Rami and Skiena, Steven},
+     title = {DeepWalk: Online Learning of Social Representations},
+     booktitle = {Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
+     series = {KDD '14},
+     year = {2014},
+     isbn = {978-1-4503-2956-9},
+     location = {New York, New York, USA},
+     pages = {701--710},
+     numpages = {10},
+     url = {http://doi.acm.org/10.1145/2623330.2623732},
+     doi = {10.1145/2623330.2623732},
+     acmid = {2623732},
+     publisher = {ACM},
+     address = {New York, NY, USA},
+     keywords = {deep learning, latent representations, learning with partial labels, network classification, online learning, social networks},
     } 
 
-
 Misc
 ----
 
@@ -85,4 +96,4 @@ DeepWalk - Online learning of social representations.
         :target: https://travis-ci.org/phanein/deepwalk
 
 .. image:: https://pypip.in/d/deepwalk/badge.png
-        :target: https://pypi.python.org/pypi/deepwalk
\ No newline at end of file
+        :target: https://pypi.python.org/pypi/deepwalk