Abstract: Technologies are described herein for probabilistically assigning weights to word senses and hypernyms of a word. The weights can be used in natural language processing applications such as information indexing and querying. A word hypernym weight (WHW) score can be determined by summing word sense probabilities of word senses from which the hypernym is inherited. WHW scores can be used to prune away hypernyms prior to indexing, to rank query results, and for other functions related to information indexing and querying. A semantic search technique can use WHW scores to retrieve an entry related to a word from an index in response to matching an indexed hypernym of the word with a query term applied to the index. More refined and accurate query results may be provided based on reduced user inputs.

Abstract: Word sense probabilities are compressed for storage in a semantic index. Each word sense for a word is mapped to one of a number of “buckets” by assigning a bucket score to the word sense. A scoring function is utilized to assign the bucket scores that maximizes the entropy of the assigned bucket scores. Once the bucket scores have been assigned to the word senses, the bucket scores are stored in the semantic index. The bucket scores stored in the semantic index may be utilized to prune one or more of the word senses prior to construction of the semantic index. The bucket scores may also be utilized to prune and rank the word senses at the time a query is performed using the semantic index.

Abstract: Word sense probabilities are compressed for storage in a semantic index. Each word sense for a word is mapped to one of a number of “buckets” by assigning a bucket score to the word sense. A scoring function is utilized to assign the bucket scores that maximizes the entropy of the assigned bucket scores. Once the bucket scores have been assigned to the word senses, the bucket scores are stored in the semantic index. The bucket scores stored in the semantic index may be utilized to prune one or more of the word senses prior to construction of the semantic index. The bucket scores may also be utilized to prune and rank the word senses at the time a query is performed using the semantic index.

Abstract: Technologies are described herein for probabilistically assigning weights to word senses and hypernyms of a word. The weights can be used in natural language processing applications such as information indexing and querying. A word hypernym weight (WHW) score can be determined by summing word sense probabilities of word senses from which the hypernym is inherited. WHW scores can be used to prune away hypernyms prior to indexing, to rank query results, and for other functions related to information indexing and querying. A semantic search technique can use WHW scores to retrieve an entry related to a word from an index in response to matching an indexed hypernym of the word with a query term applied to the index. More refined and accurate query results may be provided based on reduced user inputs.