Computer-implemented system and method for trustless zero-knowledge contingent payment
US-2024249280-A1 · Jul 25, 2024 · US
US2016196334A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2016196334-A1 |
| Application number | US-201615052151-A |
| Country | US |
| Kind code | A1 |
| Filing date | Feb 24, 2016 |
| Priority date | Jan 2, 2015 |
| Publication date | Jul 7, 2016 |
| Grant date | — |
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An approach is provided for automatically ingesting additional corpus based on an interaction history that is mined to identify a question that meets specified answer deficiency criteria, and then generate a second question which is correlated to the first question by requesting additional answer information for answering the first question, where the second question is posted to a forum using a selected persona so that forum responses can be monitored and ingested as additional content in the knowledge base.
Opening claim text (preview).
1 . A method, in an information handling system comprising a processor and a memory, for ingesting additional content in a knowledge base, the method comprising: mining, by the system, an interaction history comprising a plurality of questions and answer results to identify a first question that meets specified answer deficiency criteria; generating, by the system, a second question which is correlated to the first question by requesting additional answer information for answering the first question; selecting, by the system, at least one persona to post the second question; posting, by the system, the second question to a forum using the at least one persona; monitoring, by the system, the forum for responses to the second question; and ingesting, by the system, any response to the second question as additional content in the knowledge base. 2 . The method of claim 1 , wherein mining the interaction history comprises performing, by the system, a natural language processing (NLP) analysis of the plurality of questions and answer results, wherein the NLP analysis identifies the first question by detecting an answer for the first question that has a confidence measure below a minimum confidence threshold, by detecting an answer for the first question that provides no response, by detecting an answer for the first question that has an associated negative sentiment, or by detecting an answer for the first question that has no supporting evidence. 3 . The method of claim 1 , wherein generating the second question comprises: retrieving, by the system, one or more documents associated with the identified first question; extracting, by the system, a text sentence from the one or more documents which is correlated to the first question; and generating, by the system, the second question by parsing the text sentence to populate a defined question template used to construct the second question. 4 . The method of claim 1 , where selecting the at least one persona comprises selecting a persona from a group consisting of a primed persona, a curated persona, an automated persona, and a selected persona. 5 . The method of claim 1 , where the at least one persona is registered at the forum where the second question is posted. 6 . The method of claim 1 , further comprising generating, by the system, one or more persona associated with a selected forum by extracting user profile information from users registered with the selected forum. 7 . The method of claim 1 , further comprising generating, by the system, one or more question templates associated with a selected forum by using machine learning processing to identify one or more questions from users registered with the selected forum and extract therefrom one or more question templates. 8 - 20 . (canceled)
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