Twitter, Inc.

Microsoft Technology Licensing, LLC

Rion Langley Snow

Gilad Avraham Mishne

Scott A Waterman

Giovanni Lorenzo Thione

Barney Pell

Chad P Walters

Timothy McDonnell Converse

A method of operating a messaging platform, including: obtaining, for a first profile, a first and a second topic of interest, a first intra-profile (IP) weight for the first topic of interest, and a second IP weight for the second topic of interest; obtaining a first plurality of trending entities for the first topic and a first plurality of intra-topic (IT) weights for the first plurality of trending entities; obtaining a second plurality of trending entities for the second topic and a second plurality of IT weights for the second plurality of trending entities; selecting a subset of the first plurality of trending entities and the second plurality of trending entities based on the first IP weight, the second IP weight, the first plurality of IT weights, and the second plurality of IT weights; and sending content associated with the subset for display to a user of the first profile.

Trends in a messaging platform

A method of operating a messaging platform, including: obtaining, for a first profile of the messaging platform, a trending entity within a first topic of interest to the first profile; accessing a first plurality of messages classified as the first topic of interest; retrieving a subset of the first plurality of messages corresponding to the trending entity; and sending content associated with the subset for display to a user of the first profile.

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.

Natural language hypernym weighting for word sense disambiguation

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.

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Rion Langley Snow