Clarabridge, Inc.

Kenneth Robert Voorhees

Thomas Mathew

Fabrice Martin

Ram Ramachandran

Ellen Loeshelle

Maksym Shcherbina

Keegan Brenneman

Ramy Zulficar

Systems and methods provide a flexible environment for intelligently scoring transactions from data sources. An example method includes providing a user interface configured to generate a rubric by receiving selection of one or more one or more conditions, each condition identifying a tag generated by a classifier in the library of classifiers and for each identified tag, receiving selection of a value for the tag that satisfies the condition and receiving selection of an outcome attribute for the condition. The outcome attribute may be a weight for the tag or an alert condition. The method includes storing the rubric in a data store and applying the stored rubric to scoring units of a transaction. The method also includes aggregating scores for transactions occurring during a trend period and displaying the trend score. In some implementations, at least one classifier in the library is a rule-based classifier defined by a user.

Intelligent transaction scoring

This apparatus provides a system and method of determining significant repeating themes in a collection of documents. The apparatus operates unsupervised and leverages a natural language processing mechanism supported with lexicon, synonym and taxonomy dictionaries to determine themes and establish their relevance using a two-level hierarchical structure. The apparatus also assigns meaningful names to identified themes and determines a set of rules that describe the theme such that it can be applied to categorize other documents outside of the collection as well.

Apparatus for automatic theme detection from unstructured data

A system and method of identifying root cause of an observation by leveraging features from unstructured data is disclosed. A report generation component may be configured to generate a report. A report presentation component may be configured to allow an operator to select an observation from the report. A root cause component may be configured to determine one or more causal factors associated with the observation.

Apparatus for identifying root cause using unstructured data

Growing community of inventors

Vienna, VA, United States of America

Kenneth Robert Voorhees