Few Typo fixes

simclusters-ann/README.md

@@ -15,7 +15,7 @@ SimClusters from the Linear Algebra Perspective discussed the difference between
  However, calculating the cosine similarity between two Tweets is pretty expensive in Tweet candidate generation. In TWISTLY, we scan at most 15,000 (6 source tweets * 25 clusters * 100 tweets per clusters) tweet candidates for every Home Timeline request. The traditional algorithm needs to make API calls to fetch 15,000 tweet SimCluster embeddings. Consider that we need to process over 6,000 RPS, it’s hard to support by the existing infrastructure.  
 
 
-## SimClusters Approximate Cosine Similariy Core Algorithm
+## SimClusters Approximate Cosine Similarity Core Algorithm
 
 1. Provide a source SimCluster Embedding *SV*, *SV = [(SC1, Score), (SC2, Score), (SC3, Score) …]*
 

src/thrift/com/twitter/search/common/ranking/ranking.thrift

@@ -306,7 +306,7 @@ struct ThriftFacetRankingOptions {
   // penalty for keyword stuffing
   60: optional i32 multipleHashtagsOrTrendsPenalty
 
-  // Langauge related boosts, similar to those in relevance ranking options. By default they are
+  // Language related boosts, similar to those in relevance ranking options. By default they are
   // all 1.0 (no-boost).
   // When the user language is english, facet language is not
   11: optional double langEnglishUIBoost = 1.0

src/thrift/com/twitter/search/earlybird/thrift/earlybird.thrift

@@ -728,7 +728,7 @@ struct ThriftSearchResultMetadata {
   29: optional double parusScore
 
   // Extra feature data, all new feature fields you want to return from Earlybird should go into
-  // this one, the outer one is always reaching its limit of the nubmer of fields JVM can
+  // this one, the outer one is always reaching its limit of the number of fields JVM can
   // comfortably support!!
   86: optional ThriftSearchResultExtraMetadata extraMetadata
 
@@ -831,7 +831,7 @@ struct ThriftSearchResult {
   12: optional list<hits.ThriftHits> cardTitleHitHighlights
   13: optional list<hits.ThriftHits> cardDescriptionHitHighlights
 
-  // Expansion types, if expandResult == False, the expasions set should be ignored.
+  // Expansion types, if expandResult == False, the expansions set should be ignored.
   8: optional bool expandResult = 0
   9: optional set<expansions.ThriftTweetExpansionType> expansions
 
@@ -971,7 +971,7 @@ struct ThriftTermStatisticsResults {
   // The binIds will correspond to the times of the hits matching the driving search query for this
   // term statistics request.
   // If there were no hits matching the search query, numBins binIds will be returned, but the
-  // values of the binIds will not meaninfully correspond to anything related to the query, and
+  // values of the binIds will not meaningfully correspond to anything related to the query, and
   // should not be used. Such cases can be identified by ThriftSearchResults.numHitsProcessed being
   // set to 0 in the response, and the response not being early terminated.
   3: optional list<i32> binIds
@@ -1097,8 +1097,8 @@ struct ThriftSearchResults {
   // Superroots' schema merge/choose logic when returning results to clients:
   // . pick the schema based on the order of: realtime > protected > archive
   // . because of the above ordering, it is possible that archive earlybird schema with a new flush
-  //   verion (with new bit features) might be lost to older realtime earlybird schema; this is
-  //   considered to to be rare and accetable because one realtime earlybird deploy would fix it
+  //   version (with new bit features) might be lost to older realtime earlybird schema; this is
+  //   considered to to be rare and acceptable because one realtime earlybird deploy would fix it
   21: optional features.ThriftSearchFeatureSchema featureSchema
 
   // How long it took to score the results in earlybird (in nanoseconds). The number of results

src/thrift/com/twitter/simclusters_v2/abuse.thrift

@@ -29,8 +29,8 @@ struct AdhocSingleSideClusterScores {
 * we implement will use search abuse reports and impressions. We can build stores for new values
 * in the future.
 *
-* The consumer creates the interactions which the author recieves.  For instance, the consumer
-* creates an abuse report for an author. The consumer scores are related to the interation creation
+* The consumer creates the interactions which the author receives.  For instance, the consumer
+* creates an abuse report for an author. The consumer scores are related to the interaction creation
 * behavior of the consumer. The author scores are related to the whether the author receives these
 * interactions.
 *

src/thrift/com/twitter/simclusters_v2/embedding.thrift

@@ -70,7 +70,7 @@ struct TweetTopKTweetsWithScore {
 /**
   * The generic SimClustersEmbedding for online long-term storage and real-time calculation.
   * Use SimClustersEmbeddingId as the only identifier.
-  * Warning: Doesn't include modelversion and embedding type in the value struct.
+  * Warning: Doesn't include model version and embedding type in the value struct.
   **/
 struct SimClustersEmbedding {
   1: required list<SimClusterWithScore> embedding

src/thrift/com/twitter/simclusters_v2/evaluation.thrift

@@ -50,7 +50,7 @@ struct CandidateTweets {
 }(hasPersonalData = 'true')
 
 /**
- * An encapuslated collection of reference tweets
+ * An encapsulated collection of reference tweets
  **/
 struct ReferenceTweets {
   1: required i64 targetUserId(personalDataType = 'UserId')

src/thrift/com/twitter/simclusters_v2/identifier.thrift

@@ -33,12 +33,12 @@ enum EmbeddingType {
   Pop10000RankDecay11Tweet = 31,
   OonPop1000RankDecayTweet = 32,
 
-  // [Experimental] Offline generated produciton-like LogFavScore-based Tweet Embedding
+  // [Experimental] Offline generated production-like LogFavScore-based Tweet Embedding
   OfflineGeneratedLogFavBasedTweet = 40,
 
   // Reserve 51-59 for Ads Embedding
-  LogFavBasedAdsTweet = 51, // Experimenal embedding for ads tweet candidate
-  LogFavClickBasedAdsTweet = 52, // Experimenal embedding for ads tweet candidate
+  LogFavBasedAdsTweet = 51, // Experimental embedding for ads tweet candidate
+  LogFavClickBasedAdsTweet = 52, // Experimental embedding for ads tweet candidate
 
   // Reserve 60-69 for Evergreen content
   LogFavBasedEvergreenTweet = 60,
@@ -104,7 +104,7 @@ enum EmbeddingType {
   //Reserved 401 - 500 for Space embedding
   FavBasedApeSpace = 401 // DEPRECATED
   LogFavBasedListenerSpace = 402 // DEPRECATED
-  LogFavBasedAPESpeakerSpace = 403 // DEPRCATED
+  LogFavBasedAPESpeakerSpace = 403 // DEPRECATED
   LogFavBasedUserInterestedInListenerSpace = 404 // DEPRECATED
 
   // Experimental, internal-only IDs