Updating the K-NN Filters documentation due to recent enhancements in…

_search-plugins/knn/filter-search-knn.md

@@ -13,7 +13,7 @@ To refine k-NN results, you can filter a k-NN search using one of the following
 
 - [Efficient k-NN filtering](#efficient-k-nn-filtering): This approach applies filtering _during_ the k-NN search, as opposed to before or after the k-NN search, which ensures that `k` results are returned (if there are at least `k` results in total). This approach is supported by the following engines:
   - Lucene engine with a Hierarchical Navigable Small World (HNSW) algorithm (k-NN plugin versions 2.4 and later) 
-  - Faiss engine with an HNSW algorithm (k-NN plugin versions 2.9 or later) and IVF (k-NN plugin versions 2.10 or later)
+  - Faiss engine with an HNSW algorithm (k-NN plugin versions 2.9 or later) or IVF algorithm (k-NN plugin versions 2.10 or later)
 
 -  [Post-filtering](#post-filtering): Because it is performed after the k-NN search, this approach may return significantly fewer than `k` results for a restrictive filter. You can use the following two filtering strategies for this approach:
     - [Boolean post-filter](#boolean-filter-with-ann-search): This approach runs an [approximate nearest neighbor (ANN)]({{site.url}}{{site.baseurl}}/search-plugins/knn/approximate-knn/) search and then applies a filter to the results. The two query parts are executed independently, and then the results are combined based on the query operator (`should`, `must`, and so on) provided in the query. 
@@ -25,7 +25,7 @@ The following table summarizes the preceding filtering use cases.
 
 Filter | When the filter is applied | Type of search | Supported engines and methods | Where to place the `filter` clause
 :--- | :--- | :--- | :---
-Efficient k-NN filtering | During search (a hybrid of pre- and post-filtering) | Approximate | - `lucene` (`hnsw`) <br> - `faiss` (`hnsw`, `IVF`) | Inside the k-NN query clause.
+Efficient k-NN filtering | During search (a hybrid of pre- and post-filtering) | Approximate | - `lucene` (`hnsw`) <br> - `faiss` (`hnsw`, `ivf`) | Inside the k-NN query clause.
 Boolean filter | After search (post-filtering) | Approximate | - `lucene`<br> - `nmslib`<br> - `faiss` | Outside the k-NN query clause. Must be a leaf clause.
 The `post_filter` parameter | After search (post-filtering) | Approximate | - `lucene`<br> - `nmslib`<br> - `faiss` | Outside the k-NN query clause. 
 Scoring script filter | Before search (pre-filtering) | Exact | N/A | Inside the script score query clause.
@@ -261,16 +261,16 @@ For more ways to construct a filter, see [Constructing a filter](#constructing-a
 
 ### Faiss k-NN filter implementation 
 
-Starting with k-NN plugin version 2.9, you can use `faiss` filters for k-NN searches for HNSW algorithm and with plugin version 2.10 you can do filtering with `IVF` algorithm too.
+For k-NN searches, you can use `faiss` filters with an HNSW algorithm (k-NN plugin versions 2.9 or later) or IVF algorithm (k-NN plugin versions 2.10 or later).
 
 When you specify a Faiss filter for a k-NN search, the Faiss algorithm decides whether to perform an exact k-NN search with pre-filtering or an approximate search with modified post-filtering. The algorithm uses the following variables:
 
 - N: The number of documents in the index.
 - P: The number of documents in the document subset after the filter is applied (P <= N).
 - k: The maximum number of vectors to return in the response.
-- R: number of results returned after doing the Filtered Approximate Nearest Neighbor Search
-- FilterThreshold: A per index level threshold defined via `knn.advanced.filtered_exact_search_threshold` setting( [Ref]({{site.url}}{{site.baseurl}}/search-plugins/knn/settings/)) to switch to exact search. (P <= FilterThreshold)
-- MaxDistanceComputations: The maximum number of distance computations allowed in exact search if FilterThreshold is not set. This value cannot be changed. 
+- R: The number of results returned after doing the Filtered Approximate Nearest Neighbor Search.
+- FT: An index-level threshold defined in the [`knn.advanced.filtered_exact_search_threshold` setting]({{site.url}}{{site.baseurl}}/search-plugins/knn/settings/) that specifies to switch to exact search.
+- MDC: The maximum number of distance computations allowed in exact search if `f` filtered threshold is not set. This value cannot be changed.
 
 The following flow chart outlines the Faiss algorithm.
 

_search-plugins/knn/settings.md

@@ -12,7 +12,7 @@ The k-NN plugin adds several new cluster settings.
 ## Cluster settings
 
 Setting | Default | Description
-:--- | :-- | :---
+:--- | :--- | :---
 `knn.algo_param.index_thread_qty` | 1 | The number of threads used for native library index creation. Keeping this value low reduces the CPU impact of the k-NN plugin, but also reduces indexing performance.
 `knn.cache.item.expiry.enabled` | false | Whether to remove native library indexes that have not been accessed for a certain duration from memory.
 `knn.cache.item.expiry.minutes` | 3h | If enabled, the idle time before removing a native library index from memory.
@@ -23,4 +23,4 @@ Setting | Default | Description
 `knn.plugin.enabled`| true | Enables or disables the k-NN plugin.
 `knn.model.index.number_of_shards`| 1 | Number of shards to use for the model system index, the OpenSearch index that stores the models used for Approximate k-NN Search.
 `knn.model.index.number_of_replicas`| 1 | Number of replica shards to use for the model system index. Generally, in a multi-node cluster, this should be at least 1 to increase stability.
-`knn.advanced.filtered_exact_search_threshold`| null | Threshold value for the filtered ids that will be used to switch to exact search during Filtered ANN Search. If number of filteredIds on a segment is less than the settings value, exact search will be done on the filtered Ids. 
+`knn.advanced.filtered_exact_search_threshold`| null | Threshold value for the filtered IDs that is used to switch to exact search during filtered ANN search. If number of filtered IDs in a segment is less than this setting's value, exact search will be done on the filtered IDs.