会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 1. 发明申请
    • CONTEXT-AWARE QUERY CLASSIFICATION
    • CONTEXT-AWARE QUERY分类
    • US20110270819A1
    • 2011-11-03
    • US12771832
    • 2010-04-30
    • Dou ShenDaxin JiangJian-Tao Sun
    • Dou ShenDaxin JiangJian-Tao Sun
    • G06F17/30
    • G06F16/9535G06F16/951
    • Query classification techniques attempt to classify user search queries in order to better understand user search intent. Understanding a user's search intent allows search engines to provide relevant content tailored to the user's interest. Unfortunately, current classification techniques do not take into account contextual information. Accordingly, as provided herein, a target query may be classified based upon contextual information. In particular, features may be extracted from contextual information and/or other sources. For example, features may be extracted from the target query, related queries, and/or invoked search results of the related queries. In this way, the target query may be classified based upon other queries performed by the user and/or search results of the queries the user found interesting. In addition, a CRF model may be utilized in classifying the target query by providing generalized parameters learned from labeled query sessions.
    • 查询分类技术尝试对用户搜索查询进行分类,以便更好地了解用户搜索意图。 了解用户的搜索意图允许搜索引擎提供针对用户兴趣定制的相关内容。 不幸的是,目前的分类技术没有考虑到上下文信息。 因此,如本文所提供的,可以基于上下文信息对目标查询进行分类。 特别地,可以从上下文信息和/或其他来源中提取特征。 例如,可以从相关查询的目标查询,相关查询和/或调用的搜索结果中提取特征。 以这种方式,可以基于用户执行的其他查询和/或用户发现有趣的查询的搜索结果对目标查询进行分类。 此外,CRF模型可以用于通过提供从标记的查询会话学习的通用参数来对目标查询进行分类。
    • 5. 发明申请
    • MINING INTENT OF QUERIES FROM SEARCH LOG DATA
    • 从搜索日志数据中挖掘查询的内容
    • US20120290575A1
    • 2012-11-15
    • US13103989
    • 2011-05-09
    • Yunhua HuDaxin JiangHang Li
    • Yunhua HuDaxin JiangHang Li
    • G06F17/30
    • G06F16/3325G06F16/9535
    • Architecture that mines intent of a query from search log data. For example, for a given query, the intent, the major URLs for the intent, and intent attributes, are found. The input is search log data and the output is a database that contains the intent of queries mined from the log data. Data mining techniques are employed to discover major intents of queries in the click-through log data of a search engine. For each query, its expanded queries are created and utilized, as well as co-clicks of the original query and expanded queries in the log data. For each query, clustering is performed on the co-click data of the query and expanded queries to find the major intents of the query.
    • 从搜索日志数据中挖掘意图的架构。 例如,对于给定的查询,找到意图,意图的主要URL和意图属性。 输入是搜索日志数据,输出是包含从日志数据挖掘的查询的意图的数据库。 采用数据挖掘技术来发现搜索引擎的点击日志数据中的查询的主要意图。 对于每个查询,其扩展的查询将被创建和使用,以及日志数据中原始查询和扩展查询的共同点击。 对于每个查询,对查询和扩展查询的共同点击数据执行聚类,以查找查询的主要意图。