diff --git a/README.md b/README.md
index ade75bb..0fb3b95 100644
--- a/README.md
+++ b/README.md
@@ -14,11 +14,14 @@
World's fastest and most memory efficient full text search library with zero dependencies.
-When it comes to raw search speed FlexSearch outperforms every single searching library out there and also provides flexible search capabilities like multi-word matching, phonetic transformations or partial matching. It also has the __most memory-efficient index__. Keep in mind that updating existing items from the index has a significant cost. When your index needs to be updated continuously then BulkSearch may be a better choice. FlexSearch also provides you a non-blocking asynchronous processing model as well as web workers to perform any updates on the index as well as queries through dedicated threads.
+When it comes to raw search speed FlexSearch outperforms every single searching library out there and also provides flexible search capabilities like multi-word matching, phonetic transformations or partial matching.
+It also has the __most memory-efficient index__. Keep in mind that updating / removing existing items from the index has a significant cost. When your index needs to be updated continuously then BulkSearch may be a better choice.
+FlexSearch also provides you a non-blocking asynchronous processing model as well as web workers to perform any updates on the index as well as queries through dedicated threads.
-Benchmark:
-- Library Comparison: https://jsperf.com/compare-search-libraries
-- BulkSearch vs. FlexSearch: https://jsperf.com/flexsearch
+Comparison:
+- Library Benchmarks
+- BulkSearch vs. FlexSearch Benchmark
+- Relevance Scoring
Supported Platforms:
- Browser
@@ -48,10 +51,10 @@ All Features:
#### Contextual Search
-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__.
+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.
The basic idea of this concept is to limit relevance by its context instead of calculating relevance through the whole (unlimited) distance.
Imagine you add a text block of some sentences to an index ID. Assuming the query includes a combination of first and last word from this text block, are they really relevant to each other?
-In this way contextual search also improves the results of relevance-based queries on large amount of text data.
+In this way contextual search also improves the results of relevance-based queries on large amount of text data.
diff --git a/test/matching.html b/test/matching.html
index 0260746..88ed35b 100644
--- a/test/matching.html
+++ b/test/matching.html
@@ -148,7 +148,7 @@ var text_data = "LIBRARY OF THE FUTURE (R) First Edition Ver. 4.02 Gulliver's Tr
var data = [];
var queries = [];
- (function(){
+ setTimeout(function(){
var start = 0;
var new_data = text_data.split('. ');
@@ -253,14 +253,15 @@ var text_data = "LIBRARY OF THE FUTURE (R) First Edition Ver. 4.02 Gulliver's Tr
payload[i] = {id: i, content: data[i]};
}
- console.time('fuse');
+ // Note: fuse adds async
+ //console.time('fuse');
var fuse = new Fuse(payload.slice(0), {
keys: ['id', 'content'],
id: 'id'
});
- console.timeEnd('fuse');
+ //console.timeEnd('fuse');
var jssearch = new JsSearch.Search('id');
jssearch.addIndex('content');
@@ -338,7 +339,7 @@ var text_data = "LIBRARY OF THE FUTURE (R) First Edition Ver. 4.02 Gulliver's Tr
}
}
- })();
+ }, 50);