Optum, Inc.

Yizhao Ni

Ramin Anushiravani

Cem Unsal

Micah David Ketola

Harsh M Maheshwari

Ayush Tomar

Fazle Shahnawaz Muhibul Karim

Ketki Savle

Zengpan Fan

Various embodiments of the present disclosure provide model-based domain-aware autocomplete techniques for generating autocomplete suggestions in a complex search domain. Example embodiments are configured to generate, using a domain-aware autocomplete model, a label for an autocomplete suggestion based on a set of keywords within an autocomplete suggestion training dataset associated with a target domain source. Example embodiments are also configured to generate, using a weak-labeling model, an updated label for the autocomplete suggestion by decorrelating the set of keywords from the label. Example embodiments are also configured to generate, using a sentence classification model, a category for the autocomplete suggestion based on the updated label. Example embodiments are also configured to, using the domain-aware autocomplete model, generate a suggestion-category pair (SCP) based on the autocomplete suggestion and the category for the autocomplete suggestion. Example embodiments are also configured for initiating performance of a search query resolution based on the SCP.

Domain-aware autocomplete

Various embodiments of the present disclosure provide computer interpretation techniques for implementing a query resolution process to improve upon traditional search resolutions within a search domain. The techniques may include generating a plurality of interaction embeddings for a plurality of textual descriptions corresponding to a plurality of interaction codes identified within an interaction dataset and a plurality of taxonomy embeddings for a plurality of taxonomy categories identified within a taxonomy dataset. The techniques may include generating similarity scores for a plurality of description-category pairs based on a comparison between the plurality of interaction embeddings and the plurality of taxonomy embeddings. The techniques may include generating an enhanced taxonomy by augmenting one or more of the plurality of taxonomy categories with one or more of the plurality of textual descriptions based on the similarity scores and initiating, using the enhanced taxonomy, the performance of a query resolution operation.

Text embedding-based search taxonomy generation and intelligent refinement

Growing community of inventors

Centennial, CO, United States of America

Yizhao Ni