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
    • 4. 发明授权
    • Visual and textual query suggestion
    • 视觉和文本查询建议
    • US08452794B2
    • 2013-05-28
    • US12369421
    • 2009-02-11
    • Linjun YangMeng WangZhengjun ZhaTao MeiXian-Sheng Hua
    • Linjun YangMeng WangZhengjun ZhaTao MeiXian-Sheng Hua
    • G06F7/00G06F17/30
    • G06F17/3064G06F17/30277G06F17/30864
    • Techniques described herein enable better understanding of the intent of a user that submits a particular search query. These techniques receive a search request for images associated with a particular query. In response, the techniques determine images that are associated with the query, as well as other keywords that are associated with these images. The techniques then cluster, for each set of images associated with one of these keywords, the set of images into multiple groups. The techniques then rank the images and determine a representative image of each cluster. Finally, the tools suggest, to the user that submitted the query, to refine the search based on user selection of a keyword and a representative image. Thus, the techniques better understand the user's intent by allowing the user to refine the search based on another keyword and based on an image on which the user wishes to focus the search.
    • 本文描述的技术能够更好地理解提交特定搜索查询的用户的意图。 这些技术接收与特定查询相关联的图像的搜索请求。 作为响应,这些技术确定与查询相关联的图像以及与这些图像相关联的其他关键词。 然后,对于与这些关键词之一相关联的每组图像,该技术将该组图像聚类成多个组。 然后,技术对图像进行排序并确定每个聚类的代表图像。 最后,工具向提交查询的用户建议,根据用户对关键字和代表图像的选择来优化搜索。 因此,这些技术通过允许用户基于另一个关键字来改进搜索并且基于用户希望集中搜索的图像来更好地理解用户的意图。
    • 9. 发明申请
    • Visual and Textual Query Suggestion
    • 视觉和文本查询建议
    • US20100205202A1
    • 2010-08-12
    • US12369421
    • 2009-02-11
    • Linjun YangMeng WangZhengjun ZhaTao MeiXian-Sheng Hua
    • Linjun YangMeng WangZhengjun ZhaTao MeiXian-Sheng Hua
    • G06F17/30
    • G06F17/3064G06F17/30277G06F17/30864
    • Techniques described herein enable better understanding of the intent of a user that submits a particular search query. These techniques receive a search request for images associated with a particular query. In response, the techniques determine images that are associated with the query, as well as other keywords that are associated with these images. The techniques then cluster, for each set of images associated with one of these keywords, the set of images into multiple groups. The techniques then rank the images and determine a representative image of each cluster. Finally, the tools suggest, to the user that submitted the query, to refine the search based on user selection of a keyword and a representative image. Thus, the techniques better understand the user's intent by allowing the user to refine the search based on another keyword and based on an image on which the user wishes to focus the search.
    • 本文描述的技术能够更好地理解提交特定搜索查询的用户的意图。 这些技术接收与特定查询相关联的图像的搜索请求。 作为响应,这些技术确定与查询相关联的图像以及与这些图像相关联的其他关键词。 然后,对于与这些关键词之一相关联的每组图像,该技术将该组图像聚类成多个组。 然后,技术对图像进行排序并确定每个聚类的代表图像。 最后,工具向提交查询的用户建议,根据用户对关键字和代表图像的选择来优化搜索。 因此,这些技术通过允许用户基于另一个关键字来改进搜索并且基于用户希望集中搜索的图像来更好地理解用户的意图。
    • 10. 发明申请
    • Object-Sensitive Image Search
    • 对象敏感图像搜索
    • US20120123976A1
    • 2012-05-17
    • US12947083
    • 2010-11-16
    • Meng WangXian-Sheng HuaYan Song
    • Meng WangXian-Sheng HuaYan Song
    • G06F15/18G06F17/30
    • G06F17/30256G06K9/6259G06N99/005
    • Methods and systems for object-sensitive image searches are described herein. These methods and systems are usable for receiving a query for an image of an object and providing a ranked list of query results to the user based on a ranking of the images. The object-sensitive image searches may generate a pre-trained multi-instance learning (MIL) model trained from free training data from users sharing images at websites to identify a common pattern of the object, and/or may generate a MIL model “on the fly” trained from pseudo-positive and pseudo-negative samples of query results to identify a common pattern of the object. As such, the user is presented with query results that include images that prominently display the object near the top of the results.
    • 本文描述了用于对象敏感图像搜索的方法和系统。 这些方法和系统可用于接收对象的图像的查询,并且基于图像的排名向用户提供排序的查询结果列表。 对象敏感图像搜索可以生成预先训练的来自在网站上共享图像的用户的免费训练数据训练的多实例学习(MIL)模型,以识别对象的共同模式,和/或可以生成MIL模型 飞行“从查询结果的伪正和伪负样本中训练,以识别对象的共同模式。 因此,向用户呈现包括在结果顶部附近显着地显示对象的图像的查询结果。