United Services Automobile Association (usaa)

William Leland Fehlman, Ii

Samantha Sprague

David Charles Hardage

Shane Michael Steinert

Rajila Vinod

George Pinkosky

People provide content such as a recorded text or audio on various platforms, such as recorded telephone lines, social media, or web chats. The techniques described in this patent document can be used to obtain a set of topics that characterize the words in the recorded text or audio for each platform. By identifying topics being discussed on several platforms and by correlating topics between the platforms, a multi-channel topic orchestration server can generate a timeline that shows when the topic appeared on the various platforms.

Multi-channel topic orchestrator

Disclosed herein are systems and methods capable of performing text exploration on large volume of corpus without prior knowledge in an accurate and efficient manner and may also provide any number of additional or alternative benefits and advantages. In particular, embodiments described herein provide a text exploration executable environment that uses unsupervised machine-learning to assist a human analyst with distilling key emerging themes from a corpus of hundreds or thousands of text files presented in a time series graphical user interface (GUI). A document may be a unit of text under analysis received from a particular data source, such as word-processing documents, paragraphs, sentences, chat sessions, speech-to-text call segments, online texts, social media postings (e.g., Tweets&#xae;), and other machine-readable text. In operation, a human analyst may use a text exploration software tool to identify the themes and stories within the corpus, by using integrated, synchronized GUIs that are dynamically generated by the software exploration tool.

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Williamsburg, VA, United States of America

William Leland Fehlman, Ii