Recipe creation using text analytics

Abstract

Embodiments presented herein provide techniques for generating a recipe using text analytics methods. A server application receives a search query for a specified dish (e.g., from a client computer). The application retrieves recipes relevant to the specified dish (e.g., by crawling websites on the Internet) and extracts text from each recipe. The application performs a variety of text analytics methods on the text to identify different ingredients and preparation methods in creating the dish. Additional analytics are performed to loosely predict a recipe that conforms to the search query as well as dietary restrictions of a user.

Description

CROSS-REFERENCE TO RELATED APPLICATION[0001]This application is a continuation of co-pending U.S. patent application Ser. No.14 / 170,053, filed Jan. 31, 2014. The aforementioned related patent application is herein incorporated by reference in its entirety.BACKGROUND[0002]1. Technical Field[0003]Embodiments disclosed herein relate to text analytics. More specifically, embodiments provide techniques for generating culinary recipes by applying text analytics techniques on unstructured recipe texts.[0004]2. Description of the Related Art[0005]Text information is often voluminous and unstructured. To use large amounts of text information for a particular purpose, the information often needs to be structured based on its language and content. Text analytics describes a set of linguistic, statistical, and machine learning techniques that model and structure the information content of textual sources. Such techniques process the text information to identify structures, common meanings, and ...

AI Technical Summary

Benefits of technology

This patent provides a computer-implemented method for generating a statistical model for preparing a specific dish based on a recipe request that includes specific criteria. The method involves retrieving a plurality of recipe texts from which ingredients and methods are identified, parsed, and associated with metadata. This metadata is then used to generate a statistical model that can be used to determine the likely success of the dish based on the set of criteria. The system can also generate a combination of ingredients and methods based on the statistical model and the specified criteria. The method and system provide an efficient way to develop new dishes by using existing recipe information to guide the preparation process.

Problems solved by technology

Text information is often voluminous and unstructured.

Additionally, an individual may have specific dietary needs, so the individual might have difficulty obtaining a recipe that suits these needs.

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