Book analysis and recommendation

US10503829B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10503829-B2
Application numberUS-201715782367-A
CountryUS
Kind codeB2
Filing dateOct 12, 2017
Priority dateOct 13, 2016
Publication dateDec 10, 2019
Grant dateDec 10, 2019

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Abstract

Official abstract text for this publication.

A method includes generating style values and experiential language tags (ELTs) for a plurality of books based on retrieved book content and reader reviews, respectively. The method further includes generating an ELT prediction model based on the style values and the ELTs. The ELT prediction model is configured to receive a set of style values for a new book and output a set of predicted ELTs for the new book, the set of predicted ELTs indicating predicted reader experiences with the new book. The method further includes receiving user-submitted book content from a remote user device, determining style values for the user-submitted book content, and determining a list of predicted ELTs for the user-submitted book content using the style values for the user-submitted book content and the ELT prediction model. Additionally, the method includes transmitting, to the user device, the list of predicted ELTs for the user-submitted book content.

First claim

Opening claim text (preview).

What is claimed is: 1. A method comprising: retrieving, at a computing device, book content and reader reviews for a plurality of books, wherein the book content for each book includes an author's written portion of the book; generating, at the computing device, style values for each of the plurality of books based on the retrieved book content, wherein the style values for each book indicate the author's writing style for the book; generating, at the computing device, experiential language tags (ELTs) for each of the plurality of books based on the retrieved reader reviews, wherein the ELTs for each book indicate one or more readers' experiences with the book; generating, at the computing device, an ELT prediction model based on the style values and the ELTs for the plurality of books, wherein the ELT prediction model is configured to receive a set of style values for a new book and output a set of predicted ELTs for the new book, the set of predicted ELTs indicating predicted reader experiences with the new book; receiving, at the computing device, user-submitted book content from a remote user device; determining, at the computing device, style values for the user-submitted book content; determining, at the computing device, a list of predicted ELTs for the user-submitted book content using the style values for the user-submitted book content and the ELT prediction model; and transmitting, to the user device, the list of predicted ELTs for the user-submitted book content. 2. The method of claim 1 , further comprising: identifying, at the computing device, a list of comparable books from the plurality of books based on the style values associated with the comparable books and the style values associated with the user-submitted book content; and transmitting, to the user device, the list of comparable books. 3. The method of claim 2 , further comprising: generating, at the computing device, a filtered list of comparable books by removing books from the list of comparable books that are not associated with predicted ELTs of the user-submitted book content; and transmitting, to the user device, the filtered list of comparable books. 4. The method of claim 2 , further comprising: arranging, at the computing device, the list of comparable books based on the ELTs associated with the comparable books and the predicted ELTs associated with the user-submitted book content; and transmitting, to the user device, the arranged list of comparable books. 5. The method of claim 1 , wherein the style values include at least one of a readability style value and a writing density style value. 6. The method of claim 1 , wherein the ELTs include one or more words describing an emotional experience. 7. The method of claim 1 , wherein the ELTs include one or more words describing qualities of the book that create an experience for the readers. 8. The method of claim 1 , wherein generating the ELTs for each of the plurality of books comprises: identifying words included in the reader reviews for the book that match words included in an ELT dictionary; and assigning the matching words in the ELT dictionary to the book. 9. The method of claim 8 , wherein the ELT dictionary includes a set of assignable ELTs, wherein each of the assignable ELTs maps to a plurality of additional ELTs, and wherein assigning the matching words to the book comprises: mapping a subset of the matching words in the ELT dictionary to a single assignable ELT; and assigning the single assignable ELT to the book. 10. The method of claim 1 , wherein generating the ELT prediction model comprises generating a supervised machine learning model using the style values and the ELTs generated from the retrieved book content and reader reviews. 11. A system comprising: a book data store configured to store a plurality of book records for a plurality of books; and one or more computing devices configured to: retrieve book content and reader reviews for the plurality of books, wherein the book content for each book includes an author's written portion of the book; generate style values for each of the plurality of books based on the retrieved book content, wherein the style values for each book indicate the author's writing style for the book; generate experiential language tags (ELTs) for each of the plurality of books based on the retrieved reader reviews, wherein the ELTs for each book indicate one or more readers' experiences with the book; store the generated style values and generated ELTs in the book records; generate an ELT prediction model based on the style values and ELTs for the plurality of books, wherein the ELT prediction model is configured to receive a set of style values for a new book and output a set of predicted ELTs for the new book, the set of predicted ELTs indicating predicted reader experiences with the new book; receive user-submitted book content from a remote user device; determine style values for the user-submitted book content; determine a list of predicted ELTs for the user-submitted book content using the style values for the user-submitted book content and the ELT prediction model; and transmit, to the user device, the list of predicted ELTs for the user-submitted book content. 12. The system of claim 11 , wherein the one or more computing devices are configured to: identify a list of comparable books from the plurality of books based on the style values associated with the comparable books and the style values associated with the user-submitted book content; and transmit, to the user device, the list of comparable books. 13. The system of claim 12 , wherein the one or more computing devices are configured to: generate a filtered list of comparable books by removing books from the list of comparable books that are not associated with predicted ELTs of the user-submitted book content; and transmit, to the user device, the filtered list of comparable books. 14. The system of claim 12 , wherein the one or more computing devices are configured to: arrange the list of comparable books based on the ELTs associated with the comparable books and the predicted ELTs associated with the user-submitted book content; and transmit, to the user device, the arranged list of comparable books. 15. The system of claim 11 , wherein the style values include at least one of a readability style value and a writing density style value. 16. The system of claim 11 , wherein the ELTs include one or more words describing an emotional experience. 17. The system of claim 11 , wherein the ELTs include one or more words describing qualities of the book that create an experience for the readers. 18. The system of claim 11 , wherein the one or more computing devices are configured to generate the ELTs for each of the plurality of books by: identifying words included in the reader reviews for the book that match words included in an ELT dictionary; and assigning the matching words in the ELT dictionary to the book. 19. The system of claim 18 , wherein the ELT dictionary includes a set of assignable ELTs, wherein each of the assignable ELTs maps to a plurality of additional ELTs, and wherein the one or more computing devices are configured to assign the matching words to the book by: mapping a subset of the matching words in the ELT dictionary to a single assignable ELT; and assigning the single assignable ELT to the book. 20. The system of claim 11 , wherein the one or more computing devices are configured to generate

Assignees

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Classifications

  • Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound · CPC title

  • Combinations of networks · CPC title

  • Dictionaries · CPC title

  • Clustering; Classification · CPC title

  • Search customisation based on user profiles and personalisation · CPC title

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What does patent US10503829B2 cover?
A method includes generating style values and experiential language tags (ELTs) for a plurality of books based on retrieved book content and reader reviews, respectively. The method further includes generating an ELT prediction model based on the style values and the ELTs. The ELT prediction model is configured to receive a set of style values for a new book and output a set of predicted ELTs f…
Who is the assignee on this patent?
Booxby Inc, Univ Houston System
What technology area does this patent fall under?
Primary CPC classification G06F40/253. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Dec 10 2019 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 1 related publication on this page (citations in our corpus or others sharing the same primary CPC).