公开(公告)号：US20160253598A1

公开(公告)日：2016-09-01

申请号：US14634515

申请日：2015-02-27

Applicant: Yahoo! Inc.

Inventor： Makoto Yamada ,  Chao Qin ,  Hua Ouyang ,  Achint Thomas ,  Yi Chang

IPC: G06N99/00

CPC classification number: G06N20/00 ,  G06F21/552

Abstract: In one embodiment, a set of training data consisting of inliers may be obtained. A supervised classification model may be trained using the set of training data to identify outliers. The supervised classification model may be applied to generate an anomaly score for a data point. It may be determined whether the data point is an outlier based, at least in part, upon the anomaly score.

Abstract translation: 在一个实施例中，可以获得由内联组成的一组训练数据。 可以使用该组训练数据来训练监督分类模型以识别异常值。 可以应用监督分类模型来产生数据点的异常得分。 可以至少部分地基于异常评分来确定数据点是否是异常值。

公开(公告)号：US20160110656A1

公开(公告)日：2016-04-21

申请号：US14516471

申请日：2014-10-16

Applicant: Yahoo! Inc.

Inventor： Makoto Yamada ,  Hua Ouyang ,  Yi Chang ,  Avishek Saha

IPC: G06N99/00

CPC classification number: G06N99/005 ,  G06N5/003

Abstract: A novel method and/or system of feature selection is described.

Abstract translation: 描述了一种新颖的方法和/或特征选择系统。

公开(公告)号：US20160335263A1

公开(公告)日：2016-11-17

申请号：US14959122

申请日：2015-12-04

Applicant: Yahoo! Inc.

Inventor： Dawei Yin ,  Pengyuan Wang ,  Hua Ouyang ,  Yi Chang ,  Jean-Marc Langlois

IPC: G06F17/30

CPC classification number: G06F16/24578 ,  G06F16/9535

Abstract: The present teaching relates to ranking search content. In one example, a plurality of documents is received to be ranked with respect to a query. Features are extracted from the query and the plurality of documents. The plurality of documents is ranked based on a ranking model and the extracted features. The ranking model is derived to remove one or more documents from the plurality of documents that are less relevant to the query and order remaining documents based on their relevance to the query. The ordered remaining documents are provided as a search result with respect to the query.

Abstract translation: 本教学涉及排名搜索内容。 在一个示例中，接收到相对于查询进行排名的多个文档。 从查询和多个文档中提取特征。 基于排名模型和提取的特征来对多个文档进行排名。 导出排序模型，以从多个文档中删除与查询相关性较低的一个或多个文档，并根据其与查询的相关性来订购剩余的文档。 订购的剩余文件作为查询的搜索结果提供。