Machine learning collaboration techniques
US-2024420212-A1 · Dec 19, 2024 · US
US2016012335A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2016012335-A1 |
| Application number | US-201514860880-A |
| Country | US |
| Kind code | A1 |
| Filing date | Sep 22, 2015 |
| Priority date | Apr 9, 2014 |
| Publication date | Jan 14, 2016 |
| Grant date | — |
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A mechanism is provided, in a data processing system comprising a processor and a memory configured to implement a question and answer system (QA), for utilizing temporal indicators to weight semantic values. A set of temporal characteristics is identified of a set of initial candidate answers. For each initial candidate answer in the set of initial candidate answers: a distance value is generated for each of the set of temporal characteristics of the set of initial candidate answers, a multiplier value is determined with which to weight an initial confidence score associated with the initial candidate answer using the distance value; a sentiment value is determined of the initial candidate answer, and a final weight value is determined using the multiplier value, the sentiment value, and the initial confidence score associated with the initial candidate answer. A set of temporally refined candidate answers is then provided using the determined final weight values.
Opening claim text (preview).
1 . A method, in a data processing system comprising a processor and a memory configured to implement a question and answer system (QA), for utilizing temporal indicators to weight semantic values, the method comprising: identifying a set of temporal characteristics of a set of initial candidate answers; for each initial candidate answer in the set of initial candidate answers: generating a distance value for each of the set of temporal characteristics of the set of initial candidate answers; determining a multiplier value with which to weight an initial confidence score associated with the initial candidate answer using the distance value; determining a sentiment value of the initial candidate answer; and determining a final weight value using the multiplier value, the sentiment value, and the initial confidence score associated with the initial candidate answer; and providing a set of temporally refined candidate answers using the determined final weight values. 2 . The method of claim 1 , wherein the distance value is determined based on a reference time associated with a submitted question. 3 . The method of claim 1 , wherein the multiplier value is determined using a multiplier function: Multiplier value=1/(2 distance value+0.5) 4 . The method of claim 1 , wherein the final weight value is determined using a distance function: Final Weight=Initial confidence score*Multiplier Value*Sentiment Value 5 . The method of claim 1 , wherein the sentiment value is +1 if the determined sentiment is positive. 6 . The method of claim I, wherein the sentiment value is −1 if the determined sentiment is negative. 7 . The method of claim 1 , wherein the set of temporally refined candidate answers is ranked according to the determined final weight values. 8 - 20 . (canceled)
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