Invention Grant
US07756845B2 System and method for learning a weighted index to categorize objects
有权
用于学习加权索引以分类对象的系统和方法
- Patent Title: System and method for learning a weighted index to categorize objects
- Patent Title (中): 用于学习加权索引以分类对象的系统和方法
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Application No.: US11648323Application Date: 2006-12-28
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Publication No.: US07756845B2Publication Date: 2010-07-13
- Inventor: Omid Madani , Michael James Connor
- Applicant: Omid Madani , Michael James Connor
- Applicant Address: US CA Sunnyvale
- Assignee: Yahoo! Inc.
- Current Assignee: Yahoo! Inc.
- Current Assignee Address: US CA Sunnyvale
- Agency: Hickman Palermo Truong & Becker LLP
- Main IPC: G06F17/30
- IPC: G06F17/30

Abstract:
An improved system and method is provided for learning a weighted index to categorize objects using ranked recall. In an offline embodiment, a learning engine may learn a weighted index for classifying objects using ranked recall by training during an entire initial pass of a training sequence of a collection of objects. In an online embodiment, a learning engine may learn a weighted index for classifying objects using ranked recall by dynamically updating the weighted index as each instance of the collection of objects may be categorized. Advantageously, an instance of a large collection of objects may be accurately and efficiently recalled for many large scale applications with hundreds of thousands of categories by quickly identifying a small set of candidate categories for the given instance of the object.
Public/Granted literature
- US20080162385A1 System and method for learning a weighted index to categorize objects Public/Granted day:2008-07-03
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