Sas Institute Inc.

Jared Peterson

James Allen Cox

Saratendu Sethi

Zheng Zhao

Richard Welland Crowell

Ethem F Can

Barry DeVille

Arila Barnes

Samantha DuPont

Russel Albright

Xu Yang

Xiaolong Li

Samuel Paul Leeman-Munk

Xiaozhuo Cheng

Haipeng Liu

James Tetterton

Biljana Belamaric Wilsey

An apparatus includes processor(s) to: generate a set of candidate n-grams based on probability distributions from an acoustic model for candidate graphemes of a next word most likely spoken following at least one preceding word spoken within speech audio; provide the set of candidate n-grams to multiple devices; provide, to each node device, an indication of which candidate n-grams are to be searched for within the n-gram corpus by each node device to enable searches for multiple candidate n-grams to be performed, independently and at least partially in parallel, across the node devices; receive, from each node device, an indication of a probability of occurrence of at least one candidate n-gram within the speech audio; based on the received probabilities of occurrence, identify the next word most likely spoken within the speech audio; and add the next word most likely spoken to a transcript of the speech audio.

Speech-to-analytics framework with support for large n-gram corpora

Various embodiments are generally directed to systems for summarizing data visualizations (i.e., images of data visualizations), such as a graph image, for instance. Some embodiments are particularly directed to a personalized graph summarizer that analyzes a data visualization, or image, to detect pre-defined patterns within the data visualization, and produces a textual summary of the data visualization based on the pre-defined patterns detected within the data visualization. In various embodiments, the personalized graph summarizer may include features to adapt to the preferences of a user for generating an automated, personalized computer-generated narrative. For instance, additional pre-defined patterns may be created for detection and/or the textual summary may be tailored based on user preferences. In some such instances, one or more of the user preferences may be automatically determined by the personalized graph summarizer without requiring the user to explicitly indicate them. Embodiments may integrate machine learning and computer vision concepts.

Personalized summary generation of data visualizations

A system provides image search results based on a query that includes an attribute or an association and a concept identifier. The query is input into a trained query model to define a search syntax for the query. The search syntax is submitted to an expanded annotated image database that includes a concept image of a concept identified by the concept identifier with a plurality of attributes associated with the concept and a plurality of associations associated with the concept. A query result is received based on matching the defined search syntax to one or more of the attributes or one or more of the associations. The query result includes the concept image of the concept associated with the matched one or more of the attributes or one or more of the associations. The concept image included in the received query result is presented in a display.

System for expanding image search using attributes and associations

This disclosure provides a computer-program product, system, method and apparatus for accessing a representation of a category or item and accessing a set of multiple transactions. The transactions are processed to identify items found amongst the transactions, and the items are ordered based on an information-gain heuristic. A depth-first search for a group of best association rules is then conducted using a best-first heuristic and constraints that make the search efficient. The best rules found during the search can then be displayed to a user, along with accompanying statistics. The user can then select rules that appear to be most relevant, and further analytics can be applied to the selected rules to obtain further information about the information provided by these rules.

System and methods for interactive displays based on associations for machine-guided rule creation

Systems and methods for interactive displays based on associations for machine-guided rule creation

Growing community of inventors

Cary, NC, United States of America

Jared Peterson