[incubator-hugegraph-doc] branch master updated: Update readme & add wechat code (#218)

[ji...@apache.org]

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jin pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-hugegraph-doc.git


The following commit(s) were added to refs/heads/master by this push:
     new b7a5078d Update readme & add wechat code (#218)
b7a5078d is described below

commit b7a5078d1cc2e723a9c339b7aaffa88b3c1baa67
Author: Liu Xiao <42...@users.noreply.github.com>
AuthorDate: Mon May 15 13:41:11 2023 +0800

    Update readme & add wechat code (#218)
    
    * update readme
    
    * fix address update image
---
 README.md                |  10 +++++-----
 assets/images/weixin.png | Bin 0 -> 44655 bytes
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/README.md b/README.md
index 950c9b19..a6d02264 100644
--- a/README.md
+++ b/README.md
@@ -5,14 +5,12 @@ Please visit the [contribution doc](./contribution.md) to get start, include the
 ### Summary
 
 HugeGraph is an easy-to-use, efficient, general-purpose open source graph database system(Graph Database, [GitHub project address](https://github.com/apache/hugegraph)),
-implemented the [Apache TinkerPop3](https://tinkerpop.apache.org) framework and is fully compatible with the [Gremlin](https://tinkerpop.apache.org/gremlin.html) query language,
+implemented the [Apache TinkerPop3](https://tinkerpop.apache.org) framework and is fully compatible with the [Gremlin](https://tinkerpop.apache.org/gremlin.html) query language.
 With complete toolchain components, it helps users to easily build applications and products based on graph databases. HugeGraph supports fast import of more than 10 billion vertices and edges, and provides millisecond-level relational query capability (OLTP). 
 It supports large-scale distributed graph processing (OLAP).
 
 Typical application scenarios of HugeGraph include deep relationship exploration, association analysis, path search, feature extraction, data clustering, community detection, knowledge graph, etc., and are applicable to business fields such as network security, telecommunication fraud, financial risk control, advertising recommendation, social network and intelligence Robots etc.
 
-Typical application scenarios of HugeGraph include deep relationship exploration, association analysis, path search, feature extraction, data clustering, community detection, knowledge graph, etc., and are applicable to business fields such as network security, telecommunication fraud, financial risk control, advertising recommendation, social network and intelligence Robots etc.
-
 ### Features
 
 HugeGraph supports graph operations in online and offline environments, supports batch import of data, supports efficient complex relationship analysis, and can be seamlessly integrated with big data platforms.
@@ -55,5 +53,7 @@ The functions of this system include but are not limited to:
 
 ### Contact Us
 - [Github Issues](https://github.com/apache/incubator-hugegraph/issues): Feedback on usage issues and functional requirements (priority)
-- Feedback Email: [hugegraph@googlegroups.com](mailto:hugegraph@googlegroups.com)
-- WeChat public account: HugeGraph
+- Feedback Email: [dev@hugegraph.apache.org](mailto:dev@hugegraph.apache.org)
+- WeChat public account: Apache HugeGraph, welcome to scan this QR code to follow us.
+
+<img src="./assets/images/weixin.png">
diff --git a/assets/images/weixin.png b/assets/images/weixin.png
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