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1. 发明申请

US20120271806A1 GENERATING DOMAIN-BASED TRAINING DATA FOR TAIL QUERIES 审中-公开
标题翻译：生成尾部查询的基于域的训练数据
公开(公告)号：US20120271806A1
公开(公告)日：2012-10-25
申请号：US13091145
申请日：2011-04-21
申请人： Samuel Ieong , Nina Mishra , Eldar Sadikov , Li Zhang
发明人： Samuel Ieong , Nina Mishra , Eldar Sadikov , Li Zhang
IPC分类号： G06F17/30
CPC分类号： G06F16/9535
摘要： Training data is provided for tail queries based on a phenomena in search engine user behavior—referred to herein as “domain trust”—as an indication of user preferences for individual URLs in search results returned by a search engine for tail queries. Also disclosed are methods for generating training data in a search engine by forming a collection of query+URL pairs, identifying domains in the collection, and labeling each domain. Other implementations are directed ranking search results generated by a search engine by measuring domain trust for each domain corresponding to each URL from among a plurality of URLs and then ranking each URL by its measured domain trust.
摘要翻译：根据搜索引擎用户行为（本文称为域信任）的现象，提供了针对尾部查询的训练数据，作为搜索引擎返回的用于尾部查询的搜索结果中的各个URL的用户偏好的指示。还公开了用于通过形成查询+ URL对的集合，识别集合中的域并且标记每个域来在搜索引擎中生成训练数据的方法。针对搜索引擎生成的搜索结果，通过测量来自多个URL中的每个URL的每个域的域信任，然后通过其测量的域信任对每个URL进行排序来定向其他实现。

2. 发明授权

US08423538B1 Clustering query refinements by inferred user intent 有权
标题翻译：通过推测的用户意图来聚类查询优化
公开(公告)号：US08423538B1
公开(公告)日：2013-04-16
申请号：US12938205
申请日：2010-11-02
申请人： Eldar Sadikov , Jayant Madhavan , Alon Halevy
发明人： Eldar Sadikov , Jayant Madhavan , Alon Halevy
IPC分类号： G06F7/00 , G06F17/00
CPC分类号： G06N7/005 , G06F17/30389 , G06F17/30463 , G06F17/30598 , G06F17/30958 , G06F17/30979
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for clustering query refinements. One method includes building a representation of a graph for a first query, wherein the graph has a node for the first query, a node for each of a plurality of refinements for the first query, and a node for each document in the document sets of the refinements, and wherein the graph has edges from the first query node to each of the refinement nodes, edges from the first query to each document in the respective document set of the first query, edges from each refinement to each document in the respective document set of the refinement, and edges from each refinement to each co-occurring query of the refinement. The method further includes clustering the refinements into refinement clusters by partitioning the refinement nodes in the graph into proper subsets.
摘要翻译：方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于聚类查询优化。一种方法包括构建用于第一查询的图形的表示，其中该图具有用于第一查询的节点，用于第一查询的多个细化中的每一个的节点，以及用于第一查询的文档集合中的每个文档的节点并且其中图形具有从第一查询节点到每个细化节点的边缘，从第一查询到第一查询的相应文档集合中的每个文档的边缘，每个细化的边缘到相应文档中的每个文档精确的集合，以及每个细化的边缘到精炼的每个共同查询。该方法还包括通过将图中的细化节点划分成适当的子集来将细化聚类成细化簇。

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