Method and device for determining sample labels

A technology for sample labeling and determination method, applied in the Internet field, can solve the problems of low labeling efficiency and high labor cost, save labor, reduce labor participation, and improve labeling efficiency.

Active Publication Date: 2015-01-28
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] In the multi-instance learning problem, the existing technology mainly screens and la

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  • Method and device for determining sample labels
  • Method and device for determining sample labels
  • Method and device for determining sample labels

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Embodiment Construction

[0016] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention. On the contrary, the embodiments of the present invention include all changes, modifications and equivalents coming within the spirit and scope of the appended claims.

[0017] figure 1 A flowchart of an embodiment of the determination method for sample labeling of the present invention, such as figure 1 As shown, the method for determining the sample label may include:

[0018] Step 101, extracting online feedback data to obtain initial model training data.

[0019] Step 102, extract scene features from the above initial model training...

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Abstract

The invention provides a method and a device for determining sample labels. The method for determining the sample labels comprises the following steps of extracting on-line feedback data to acquire initial model training data; extracting scene features from the initial model training data; adding the scene features into the initial model training data to acquire sample data; calculating the sample quality score of each group of sample data; labeling each group of sample data according to the corresponding sample quality score of the corresponding group of sample data; learning the labeled sample data to generate a model; and predicting labels of the sample data by using the model. In a multi-example learning problem, labor is reduced when the sample is labeled, a large amount of labor is saved, and the labeling efficiency can be improved.

Description

technical field [0001] The present invention relates to the technical field of the Internet, in particular to a method and device for determining sample labeling. Background technique [0002] In multi-instance learning, a sample is a bag composed of multiple examples. Multi-instance learning is to label samples at the granularity of the bag, and each sample contains several examples, which are not labeled. If a sample is marked as a positive example, there is at least one positive example in the sample; otherwise, if a sample is marked as a negative example, all examples in the sample are negative examples. The purpose of multi-instance learning is to make judgments on new samples as accurately as possible by learning from these labeled samples. [0003] In the multi-instance learning problem, the existing technology mainly screens and labels the samples manually. This labeling method has high labor costs and low labeling efficiency. Contents of the invention [0004] T...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F18/217G06F18/214
Inventor 胡光胡殿明刘洪魏伟
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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