公开(公告)号：US20170169251A1

公开(公告)日：2017-06-15

申请号：US14969201

申请日：2015-12-15

Applicant: Yahoo! Inc.

Inventor： Liane Lewin-Eytan ,  Dotan Di Castro ,  Eyal Zohar ,  Yoelle Maarek ,  Ran Wolff ,  Doug Sharp

IPC: G06F21/62 ,  H04L12/58 ,  G06F17/22

Abstract: Methods, systems, and computer-readable media for anonymizing electronic documents. In accordance with one or more embodiments, structurally-similar electronic documents can be identified among a group of electronic documents (e.g., e-mail messages, documents containing HTML formatting, etc.). A hash function can be specifically tailored to identify the similarly structured documents. The structurally-similar electronic documents can be grouped into a same equivalence class. Masked anonymized document samples can be generated from the structurally-similar electronic documents utilizing the same equivalence class, thereby ensuring that the anonymized document samples when viewed as a part of an audit remain anonymous. An online process is provided to guarantee k-anonymity of the users over the entire lifetime of the auditing process. An auditor's productivity can be measured based on the amount of content revealed to the auditor within the samples he is assigned. The auditor's productivity is maximized while ensuring anonymization over the lifetime of the audit.

公开(公告)号：US10146872B2

公开(公告)日：2018-12-04

申请号：US14332501

申请日：2014-07-16

Applicant: Yahoo! Inc.

Inventor： David Carmel ,  Ran Wolff

IPC: G06F17/30

Abstract: Methods, systems and programming for predicting search results quality. In one example, a search query is received from a user. A plurality of search results are obtained from a content source based on the search query. The plurality of search results are ranked based on their relevance scores with respect to the search query. A distribution of the relevance scores of the plurality of search results is normalized in each position of the ranking. A metric of the content source is computed based on the normalized distribution of the relevance scores. The metric indicates a relevance between the plurality of search results and the search query.

公开(公告)号：US20160019213A1

公开(公告)日：2016-01-21

申请号：US14332501

申请日：2014-07-16

Applicant: Yahoo! Inc.

Inventor： David Carmel ,  Ran Wolff

IPC: G06F17/30

CPC classification number: G06F17/30864

Abstract: Methods, systems and programming for predicting search results quality. In one example, a search query is received from a user. A plurality of search results are obtained from a content source based on the search query. The plurality of search results are ranked based on their relevance scores with respect to the search query. A distribution of the relevance scores of the plurality of search results is normalized in each position of the ranking. A metric of the content source is computed based on the normalized distribution of the relevance scores. The metric indicates a relevance between the plurality of search results and the search query.

Abstract translation: 用于预测搜索结果质量的方法，系统和程序设计。 在一个示例中，从用户接收到搜索查询。 基于搜索查询从内容源获得多个搜索结果。 根据搜索查询的相关性得分，对多个搜索结果进行排序。 多个搜索结果的相关性分数的分布在排名的每个位置被归一化。 基于相关性分数的归一化分布来计算内容源的度量。 该度量指示多个搜索结果和搜索查询之间的相关性。