Disambiguating unrecognized abbreviations in search queries using machine learning
US-2024070178-A1 · Feb 29, 2024 · US
Consistent phrase relevance measures
US8996515B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-8996515-B2 |
| Application number | US-201213609257-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 11, 2012 |
| Priority date | Jun 24, 2008 |
| Publication date | Mar 31, 2015 |
| Grant date | Mar 31, 2015 |
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Abstract
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Two methods for measuring keyword-document relevance are described. The methods receive a keyword and a document as input and output a probability value for the keyword. The first method is a similarity-based approach which uses techniques for measuring similarity between two short-text segments to measure relevance between the keyword and the document. The second method is a regression-based approach based on an assumption that if an out-of-document phrase (the keyword) is semantically similar to an in-document phrase, then relevance scores of the in and out-of document phrases should be close to each other.
First claim
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The invention claimed is: 1. One or more computer readable media, not comprising a signal, storing information to enable a computing device to perform a process of predicting a probability that an input out-of-document phrase that is not in a document is relevant to the document, the process comprising: applying an in-document phrase relevance measure to the target document to get a list of in-document keywords in the document and respective associated probabilities of relevance,…
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- G06F16/3346Primary
Physics · mapped topic
Physics · mapped topic
- G06F17/30687Primary
Physics · mapped topic
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Frequently asked questions
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- What does patent US8996515B2 cover?
- Two methods for measuring keyword-document relevance are described. The methods receive a keyword and a document as input and output a probability value for the keyword. The first method is a similarity-based approach which uses techniques for measuring similarity between two short-text segments to measure relevance between the keyword and the document. The second method is a regression-based a…
- Who is the assignee on this patent?
- Yih Wen-Tau, Meek Christopher A, Microsoft Corp
- What technology area does this patent fall under?
- Primary CPC classification G06F16/3346. Mapped technology areas include Physics.
- When was this patent published?
- Publication date Tue Mar 31 2015 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 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).