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Finding your new favorite books

By Veronica Salinas

A book is not just a bound piece of printed information. A book creates a relationship between authors and readers that often leads bibliophiles on a road to discovery. Researchers at UH are helping develop the literary startup, Booxby, an app that aligns users with contemporary authors based on their reading interests or experiences.

UH computer science associate professor Thamar Solorio partnered with novelist and Booxby chief executive officer Holly Payne to develop the app. Solorio is a leading expert in stylistic text analysis, a computer science concentration that examines the very minute details of a sentence.  

Mark Bregman, a member of the board of trustees for Booxby, approached Solorio about her innovative work after she won the Grace Hopper Prize from the Anita Borg Institute. Bregman sensed Solorio’s knowledge of computer science could be instrumental in the partnership with Payne.

The Booxby app is based on what experience the reader is looking for and proffers questions such as ‘How do you want to feel?’ Solorio emphasizes that there is a distinction between Booxby and other book recommendation systems. “We want to examine the content to look for a similar experience,” she says. 

Booxby was created to help readers access the work of modern authors by using stylistic text analysis. The algorithm used in the Booxby app analyzes the makeup of a book then selects authors who have written books with similar tones and characteristics.

“The main goal of Booxby is to allow writers to reach readers and allow readers to find what they’re looking for without a lot of frustration or swiping through books they’re not going to like,” said Solorio. “The second goal is to promote reading.”

Currently the Booxby team is in the first phase of development. In December 2015 they were awarded a one-year Small Business Technology Transfer grant to develop the app. They also won a 2016 National Science Foundation grant for innovation in natural language processing and machine learning. The team plans to transition to beta testing this fall with the intent to launch the app early next year.  

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