Update README.md

README.md

@@ -4,15 +4,8 @@
 ## Installation
 The package is registered in the [`General`](https://github.com/JuliaRegistries/General) registry and so can be installed at the REPL with `] add StringDistances`.
 
-## Evaluate
-To compute the distance between two strings (or between two iterators), you can use one of these two syntaxes:
-
-```julia
-evaluate(dist, s1, s2)
-dist()(s1, s2)
-```
-
-where `dist` is one of the following distances::
+## Supported Distances
+The available distances are:
 
 - Edit Distances
 	- [Jaro Distance](https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance) `Jaro()`
@@ -25,9 +18,7 @@ where `dist` is one of the following distances::
 	- [Jaccard Distance](https://en.wikipedia.org/wiki/Jaccard_index) `Jaccard(q::Int)`
 	- [Overlap Distance](https://en.wikipedia.org/wiki/Overlap_coefficient) `Overlap(q::Int)`
 	- [Sorensen-Dice Distance](https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient) `SorensenDice(q::Int)`
-
-- The package includes distance "modifiers", that can be applied to any distance.
-
+- Distance "modifiers" that can be applied to any distance:
 	- [Winkler](https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance) diminishes the distance of strings with common prefixes.  The Winkler adjustment was originally defined for the Jaro similarity score but this package defines it for any string distance.
 	- [Partial](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/) returns the minimum distance between the shorter string and substrings of the longer string.
 	- [TokenSort](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/) adjusts for differences in word orders by reording words alphabetically. 
@@ -37,29 +28,36 @@ where `dist` is one of the following distances::
 
 A good distance to match strings composed of multiple words (like addresses) is `TokenMax(Levenshtein())` (see [fuzzywuzzy](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/)
 
+
+## Basic Use
+
+### evaluate
+You can always compute a certain distance between two strings (or iterators) using the following syntax:
+
 ```julia
-evaluate(Levenshtein(), "martha", "marhta")
-evaluate(QGram(2), "martha", "marhta")
-evaluate(Winkler(Jaro()), "martha", "marhta")
-
-
-Levenshtein()("martha", "marhta")
-QGram(2)("martha", "marhta")
-Winkler(Jaro())("martha", "marhta")
+evaluate(dist, s1, s2)
+dist(s1, s2)
 ```
 
-## Compare
+For instance, with the `Levenshtein` distance,
+
+```julia
+evaluate(Levenshtein(), "martha", "marhta")
+Levenshtein()("martha", "marhta")
+```
+
+### compare
 The function `compare` is defined as 1 minus the normalized distance between two strings. It always returns a number between 0 and 1: a value of 0 means completely different and a value of 1 means completely similar.
+
 ```julia
 evaluate(Levenshtein(), "New York", "New York")
 #> 0
 compare("New York", "New York", Levenshtein())
 #> 1.0
-
 ```
 
 
-## Find
+## find
 - `findmax` returns the value and index of the element in `itr` with the highest similarity score with `s`. Its syntax is:
 	```julia
 	findmax(s, itr, dist::StringDistance; min_score = 0.0)