公开(公告)号：US20160098488A1

公开(公告)日：2016-04-07

申请号：US14966545

申请日：2015-12-11

Applicant: Google Inc.

Inventor： Alexis J. Battle ,  David Ariel Cohn ,  Carrie Elizabeth Grimes ,  John Ogden Lamping

IPC: G06F17/30

CPC classification number: G06F16/9535 ,  G06F16/951 ,  G06Q30/0201 ,  H04L67/02 ,  H04L67/22 ,  H04L67/30

Abstract: Systems and methods for deriving and using an interaction profile are described. In one described method, a plurality of metrics indicating a level of satisfaction for search results is determined. The metrics comprise at least one of click-duration data, multiple-click data, and query-refinement data. The values of the metrics for a plurality of instances of an object, such as search results from a search engine, are determined. An interaction profile for the object, based at least in part on the values of the metrics for a plurality of instances of the first object, is then determined. This interaction profile may be used in a variety of ways, such as determining the quality of ranking algorithms and detecting undesirable search results.

Abstract translation: 描述用于导出和使用交互简档的系统和方法。 在一种描述的方法中，确定指示搜索结果的满足程度的多个度量。 度量包括点击持续时间数据，多点击数据和查询细化数据中的至少一个。 确定对象的多个实例的度量的值，诸如来自搜索引擎的搜索结果。 然后，至少部分地基于第一对象的多个实例的度量的值来确定对象的交互简档。 该交互简档可以以各种方式使用，例如确定排序算法的质量并检测不期望的搜索结果。

公开(公告)号：US09697249B1

公开(公告)日：2017-07-04

申请号：US14737720

申请日：2015-06-12

Applicant: Google Inc.

Inventor： David R. Bailey ,  Alexis J. Battle ,  Benedict A. Gomes ,  P. Pandurang Nayak

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30389 ,  G06F17/3053 ,  G06F17/3064 ,  G06F17/30864 ,  Y10S707/99932 ,  Y10S707/99934 ,  Y10S707/99935

Abstract: An information retrieval system includes a query revision architecture that integrates multiple different query revisers, each implementing one or more query revision strategies. A revision server receives a user's query, and interfaces with the various query revisers, each of which generates one or more potential revised queries. The revision server evaluates the potential revised queries, and selects one or more of them to provide to the user. A session-based reviser suggests one or more revised queries, given a first query, by calculating an expected utility for the revised query. The expected utility is calculated as the product of a frequency of occurrence of the query pair and an increase in quality of the revised query over the first query.