update readme

README.md

@@ -1,14 +1,38 @@
-# RSATree
+# RSATree: Distribution-Aware Data Representation of Large-Scale Tabular Datasets for Flexible Visual Query
+
+RSATree is a novel data representation, which supports flexible approximate query of large-scale tabular datasets and interactive interface in different scenarios. The project is developed by [Visual Analytics Group](<https://zjuvag.org/>) from [State Key Lab of CAD&CG]((http://www.cad.zju.edu.cn/english.html)), Zhejiang University, China.
+
+<img src='./docs/algorithm.png'>
+
+## Citation
+
+We have written a [paper](<https://ieeexplore.ieee.org/document/8807303>) about the research behind RSAtree which was accepted by [IEEE VIS 2019](<http://ieeevis.org/year/2019/welcome>),  Please cite us if you use it in a publication.
+
+```bib
+@ARTICLE{8807303, 
+    author={H. {Mei} and W. {Chen} and Y. {Wei} and Y. {Hu} and S. {Zhou} and B. {Lin} and Y. {Zhao} and J. {Xia}}, 
+    journal={IEEE Transactions on Visualization and Computer Graphics}, 
+    title={RSATree: Distribution-Aware Data Representation of Large-Scale Tabular Datasets for Flexible Visual Query}, 
+    year={2019}, 
+    volume={}, 
+    number={}, 
+    pages={1-1}, 
+    keywords={Visualization;Data visualization;Aggregates;Histograms;Time factors;Visual databases;Social networking (online);Aggregate query;visual query;large-scale data visualization;R-tree;summed area table;hashing}, 
+    doi={10.1109/TVCG.2019.2934800}, 
+    ISSN={}, 
+    month={},
+}
+```
 
-Our coding environment is **ubuntu 18.04** with **32GB** RAM, 500GB SSD
+## Build and Run
 
-C++ version is **gcc 7.4.0**
+We are open two demos about our algorithm. 
 
-node version is **v10.16.0**
+Our coding environment is **ubuntu 18.04** with **32GB** RAM, 500GB SSD
 
-cmake version is **3.10.2**
+C++ version is **gcc 7.4.0**, node version is **v10.16.0**, cmake version is **3.10.2**
 
-### Construct
+#### Construct the data structure
 
 First you need to install a library for reading json files
 
@@ -26,7 +50,7 @@ sudo make install
 
 there is a template about how to builld BRIGHTKITE datasets using C++
 
-I have prepared a smaller binary file of BRIGHTKITE in folder data 
+I have prepared a smaller binary file of BRIGHTKITE in folder `./construct/data `
 
 ```bash
 cd construct
@@ -37,7 +61,7 @@ bash build.sh
 cp result/* ../backend/data/BRIGHTKITE
 ```
 
-### Install 
+#### Install libraries using npm
 
 ```bash
 cd frontend
@@ -48,7 +72,7 @@ npm install
 npm audit fix
 ```
 
-### Run
+#### Run the server
 
 ```bash
 # start frontend 
@@ -61,4 +85,5 @@ cd backend
 npm run start
 ```
 
-you will see the website on <http://localhost:8081/>
+you will see the website on <http://localhost:8081/>
+