[KG] a little update on readme. (#914)

* update readme.

* Update README.md

apps/kg/README.md

@@ -4,7 +4,12 @@
 ## Introduction
 
 DGL-KE is a DGL-based package for computing node embeddings and relation embeddings of
-knowledge graphs efficiently. DGL-KE is fast and scalable. On a single machine,
+knowledge graphs efficiently. This package is adapted from
+[KnowledgeGraphEmbedding](https://github.com/DeepGraphLearning/KnowledgeGraphEmbedding).
+We enable fast and scalable training of knowledge graph embedding,
+while still keeping the package as extensible as
+[KnowledgeGraphEmbedding](https://github.com/DeepGraphLearning/KnowledgeGraphEmbedding).
+On a single machine,
 it takes only a few minutes for medium-size knowledge graphs, such as FB15k and wn18, and
 takes a couple of hours on Freebase, which has hundreds of millions of edges.
 
@@ -65,6 +70,8 @@ The accuracy on FB15k
 | DistMult | 43.35 | 0.783 | 0.713  | 0.837  | 0.897   |
 | ComplEx  | 51.99 | 0.785 | 0.720  | 0.832  | 0.889   |
 
+In comparison, GraphVite uses 4 GPUs and takes 14 minutes. Thus, DGL-KE trains TransE on FB15k twice as fast as GraphVite while using much few resources. More performance information on GraphVite can be found [here](https://github.com/DeepGraphLearning/graphvite).
+
 The speed on wn18
 
 |  Models | TransE | DistMult | ComplEx |