diff --git a/README.md b/README.md
index fc9ad3a..ec0e774 100644
--- a/README.md
+++ b/README.md
@@ -40,7 +40,7 @@ You can help me by making a personal donation to keep this project alive and als
-When it comes to raw search speed FlexSearch outperforms every single searching library out there and also provides flexible search capabilities like multi-field search, phonetic transformations or partial matching.
+When it comes to raw search speed FlexSearch outperforms every single searching library out there and also provides flexible search capabilities like multi-field search, phonetic transformations or partial matching.
Depending on the used options it also provides the most memory-efficient index. FlexSearch introduce a new scoring algorithm called "contextual index" based on a pre-scored lexical dictionary architecture which actually performs queries up to 1,000,000 times faster compared to other libraries.
FlexSearch also provides you a non-blocking asynchronous processing model as well as web workers to perform any updates or queries on the index in parallel through dedicated balanced threads.
@@ -55,8 +55,8 @@ Demos:
-->
Library Comparison "Gulliver's Travels":
-- Performance Benchmark
-- Scoring Benchmark
+- Performance Benchmark
+- Scoring Benchmark
- Memory Consumption
Plugins (extern projects):
@@ -256,7 +256,7 @@ npm install flexsearch
## Performance Benchmark (Ranking)
-Run Comparison: Performance Benchmark "Gulliver's Travels"
+Run Comparison: Performance Benchmark "Gulliver's Travels"
Operation per seconds, higher is better, except the test "Memory" on which lower is better.
@@ -2188,9 +2188,9 @@ index.remove(0).update(1, 'foo').add(2, 'foobar');
> __Note:__ This feature is disabled by default because of its extended memory usage. Read here get more information about and how to enable.
-FlexSearch introduce a new scoring mechanism called __Contextual Search__ which was invented by Thomas Wilkerling, the author of this library. A Contextual Search incredibly boost up queries to a complete new level but also requires some additional memory (depending on ___depth___).
+FlexSearch introduce a new scoring mechanism called __Contextual Search__ which was invented by Thomas Wilkerling, the author of this library. A Contextual Search incredibly boost up queries to a complete new level but also requires some additional memory (depending on ___depth___).
The basic idea of this concept is to limit relevance by its context instead of calculating relevance through the whole distance of its corresponding document.
-This way contextual search also improves the results of relevance-based queries on a large amount of text data.
+This way contextual search also improves the results of relevance-based queries on a large amount of text data.
