Patent
Context based text prediction
Jannes Dolfing,Brent D. Ramerth,Douglas R. Davidson,Jerome R. Bellegarda,Jennifer Moore,Andreas Eminidis,Joshua H. Shaffer +6 more
- 26 May 2015
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TL;DR: In this paper, a text input can be associated with an input context and a weighting factor can be determined based on a degree of similarity between the input contexts and the context.
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Abstract: Systems and processes for predictive text input are provided In one example process, a text input can be received The text input can be associated with an input context A frequency of occurrence of an m-gram with respect to a subset of a corpus can be determined using a language model The subset can be associated with a context A weighting factor can be determined based on a degree of similarity between the input context and the context A weighted probability of a predicted text given the text input can be determined based on the frequency of occurrence of the m-gram and the weighting factor The m-gram can include at least one word in the text input and at least one word in the predicted text
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Citations
Patent
Word order suggestion taking into account frequency and formatting information
Andrew Nicholas Paul Smith
- 30 Jul 2019
TL;DR: In this article, the authors describe processing that improves suggestions for a misspelt word based on an analysis of an unformatted state of content within an electronic document and an analysisof formatting associated with content of the electronic document.
1
References
Patent
Nonstandard locality-based text entry
Shumeet Baluja
- 30 Jun 2006
TL;DR: A computer-implemented method of providing text entry assistance data includes receiving at a system location information associated with a user, receiving at the system information indicative of predictive textual outcomes, generating dictionary data using the location information, and providing the dictionary data to a remote device as discussed by the authors.
131
Patent
Text prediction using environment hints
Zachary H. Jones,Aaron J. Quirk,Lin Sun +2 more
- 20 Aug 2013
TL;DR: In this paper, a list of words is received, where each word in the list has an associated weight, and the associated weight of the at least one word is updated using the obtained environment weight.
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