Abstract: Systems and methods for training a personalized Machine Learning (ML) model used to detect fall events are described herein. The methods may be implemented by one or more computing devices and may include obtaining sensor data associated with one or more activities of a user. A processed or unprocessed version of at least a copy of the sensor data having been fed to a personalized ML model associated with the user and that has been determined not to be associated with a fall event; and using the obtained sensor data training the personalized ML model.

Abstract: The present invention provides systems and methods that employ a statistical distributional analysis to improve content search engine search results. In particular, a substring and/or a string sequence distributional algorithm can be applied to a set of queries to generate a distributional characteristic (e.g., a profile) for the set of queries, wherein the set is selected from a plurality of queries stored on a query log. Typically, the queries are selected based on a substring of interest and/or an identification of a user initiating searches. The distributional characteristic can then be employed to determine a distributional similarity measure that can be utilized in connection with a search to facilitate search results via providing a mechanism to determine synonymous search terms, spelling corrections/variations, and facilitate collaborative filtering, for example. Thus, the present invention employs a novel technique that mines and employs previous queries to enhance the query search results.

Abstract: The present invention provides systems and methods that employ a statistical distributional analysis to improve content search engine search results. In particular, a substring and/or a string sequence distributional algorithm can be applied to a set of queries to generate a distributional characteristic (e.g., a profile) for the set of queries, wherein the set is selected from a plurality of queries stored on a query log. Typically, the queries are selected based on a substring of interest and/or an identification of a user initiating searches. The distributional characteristic can then be employed to determine a distributional similarity measure that can be utilized in connection with a search to facilitate search results via providing a mechanism to determine synonymous search terms, spelling corrections/variations, and facilitate collaborative filtering, for example. Thus, the present invention employs a novel technique that mines and employs previous queries to enhance the query search results.