diff --git a/docs/Documentation-CHN/UserGuideV0.7.0/2-Concept Key Concepts and Terminology/3-Encoding.md b/docs/Documentation-CHN/UserGuideV0.7.0/2-Concept Key Concepts and Terminology/3-Encoding.md
index 3c6c4c881c29b2cb7f9a6122deea9a331592f099..8b0130ed139644c28b801e068a2fab5d1d994407 100644
--- a/docs/Documentation-CHN/UserGuideV0.7.0/2-Concept Key Concepts and Terminology/3-Encoding.md	
+++ b/docs/Documentation-CHN/UserGuideV0.7.0/2-Concept Key Concepts and Terminology/3-Encoding.md	
@@ -45,11 +45,11 @@ PLAIN编码，默认的编码方式，即不编码，支持多种数据类型，
 
 GORILLA编码，比较适合编码前后值比较接近的浮点数序列，不适合编码前后波动较大的数据。
 
-* 规则数据编码 (REGULAR)
+* 定频数据编码 (REGULAR)
 
-规则数据编码, 比较适合于编码规则序列递增的数据(例如，每个数据点之间经过相同时间的时间序列)，在这种情况下，它的性能将优于二阶插分 (TS_2DIFF) 编码。
+定频数据编码，仅适用于整形（INT32）和长整型（INT64）的定频数据，且允许数据中有一些点缺失，使用此方法编码定频数据优于二阶差分编码（TS_2DIFF）。
 
-规则数据编码不适用于有波动(不规则数据)的数据，建议使用二阶差分编码 (TS_2DIFF) 进行处理。
+定频数据编码无法用于非定频数据，建议使用二阶差分编码（TS_2DIFF）进行处理。
 
 * 数据类型与编码的对应关系
 
diff --git a/docs/Documentation/UserGuideV0.7.0/2-Concept Key Concepts and Terminology/3-Encoding.md b/docs/Documentation/UserGuideV0.7.0/2-Concept Key Concepts and Terminology/3-Encoding.md
index 3b3c7cd72e997b7810666e0b0f6fbf7b037de147..c9fdc3c6d3cde822c7a231f9e956458763b9f2bf 100644
--- a/docs/Documentation/UserGuideV0.7.0/2-Concept Key Concepts and Terminology/3-Encoding.md	
+++ b/docs/Documentation/UserGuideV0.7.0/2-Concept Key Concepts and Terminology/3-Encoding.md	
@@ -7,9 +7,9 @@
     to you under the Apache License, Version 2.0 (the
     "License"); you may not use this file except in compliance
     with the License.  You may obtain a copy of the License at
-    
+
         http://www.apache.org/licenses/LICENSE-2.0
-    
+
     Unless required by applicable law or agreed to in writing,
     software distributed under the License is distributed on an
     "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
@@ -46,9 +46,9 @@ GORILLA encoding is more suitable for floating-point sequence with similar value
 
 * REGULAR
 
-Regular data encoding is more suitable for encoding regular sequence increasing data (e.g. the timeseries with the same time elapsed between each data point), which its performance would be better than TS_2DIFF in this situation.
+Regular data encoding is more suitable for encoding regular sequence increasing data (e.g. the timeseries with the same time elapsed between each data point), in which case it's better than TS_2DIFF.
 
-Regular data encoding method is not suitable for the data with fluctuations (irregular data), which is recommended to use the TS_2DIFF encoder to deal with it.
+Regular data encoding method is not suitable for the data with fluctuations (irregular data), and TS_2DIFF is recommended to deal with it.
 
 * Correspondence between data type and encoding