# US 2020/0401655 A1 · Automated generation of related subject matter footer links and previously answered questions > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2020/0401655 A1 - Document ID: US20200401655A1 - Status: Published application - Kind: A1 - Application number: 16/446,117 - Filed: 2019-06-19 - Published: 2020-12-24 - Earliest claimed: 2019-06-19 - Assignees: Wyzant, Inc. - Applicants: Wyzant, Inc. - Inventors: Benjamin Listyg; Edward Corcoran; Michael Angellotti; Brent Zajaczkowski; Jonathan Gostelow; Jorel Casal; David Jaress - Web page: https://patentgrep.com/patent/US20200401655A1 ## CPC - G06F 40/134: Hyperlinking - G06F 40/166: Editing, e.g. inserting or deleting - G06F 40/169: Annotation, e.g. comment data or footnotes - G06F 40/205: Parsing - G06Q 50/20: Education - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract A system and method for utilizing automatically generating related subject matter areas to create footer links for a subject matter page of a tutor matching website is disclosed and claimed. In particular, a document embedding algorithm such as word2vec, doc2vec or GloVe can be trained using on a particular subject using pertinent material such as, for example, textbooks, learned papers, and transcripts of lectures. Once trained, the document embedding algorithm can be used to generate a list of related subjects that can be used to automatically build footer links for a particular subject matter page. The related footer links can improve the positioning of the tutor matching website with common Internet search engines. The same document embedding algorithm can be used to identify previously answered questions that may assist a user posing a question to the tutor matching website. ## Claims ### Claim 1 A computer-implemented method for use with a tutor matching website, the method generating footer links for a subject matter webpage, the subject matter webpage being associated with a particular subject, the method performed by at least one processor comprising the steps of: accepting the particular subject; executing a related subject matter algorithm on the particular subject to generate a list of related subjects, the list comprising at least one entry identifying a related subject; generating a footer link for the at least one entry, with the footer link corresponding to the related subject; appending the footer link to a footer of the subject matter webpage. ### Claim 2 (depends on 1) The method of claim 1 wherein the footer link points to an internal webpage. ### Claim 3 (depends on 1) The method of claim 1 wherein the footer link is an inactive link. ### Claim 4 (depends on 1) The method of claim 1 wherein the footer link is appended to the footer of the subject matter webpage in the order that it was processed. ### Claim 5 (depends on 1) The method of claim 1 wherein the footer link is appended to the footer of the subject matter webpage in an alphabetical order. ### Claim 6 (depends on 1) The method of claim 1 wherein the footer link is appended to the footer of the subject matter webpage in an order based on a relatedness index returned by the related subject matter algorithm. ### Claim 7 (depends on 1) The method of claim 1 wherein the related subject matter algorithm is a document embedding algorithm. ### Claim 8 (depends on 7) The method of claim 7 wherein the related subject matter algorithm is selected from the group consisting of word2vec, doc2vec or GloVe. ### Claim 9 A computer-implemented method for use with a tutor matching website, the method generating a list of previously answered related questions in response to a user entering a new question, the new question being associated with a particular subject, the method performed by at least one processor comprising the steps of: accepting the new question; constructing a custom answered question page; parsing the question to determine a primary subject; executing a related subject matter algorithm on the particular subject to generate a list of related subjects, the list comprising at least one entry identifying a related subject; retrieving one or more previously answered questions corresponding to the related subject; and appending the one or more previously answered questions to the custom answered question page. ### Claim 10 (depends on 9) The method of claim 9 wherein the step of executing generates a relevance index for the at least one entry identifying a related subject, and wherein the step of appending utilizes the relevance index when appending the one or more previously answered questions to the custom answered question page so that the previously questions corresponding to a most relevant subject are placed at a top portion of the custom answered question page. ### Claim 11 (depends on 9) The method of claim 9 wherein the related subject matter algorithm is a document embedding algorithm. ### Claim 12 (depends on 11) The method of claim 11 wherein the related subject matter algorithm is selected from the group consisting of word2vec, doc2vec or GloVe.