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    • 1. 发明授权
    • In-text embedded advertising
    • 文字内嵌广告
    • US08352321B2
    • 2013-01-08
    • US12334364
    • 2008-12-12
    • Tao MeiXian-Sheng HuaShipeng LiLinjun Yang
    • Tao MeiXian-Sheng HuaShipeng LiLinjun Yang
    • G06Q30/00
    • G06Q30/0251G06F17/27G06F17/3089G06Q30/02G06Q30/0277
    • Computer program products, devices, and methods for generating in-text embedded advertising are described. Embedded advertising is “hidden” or embedded into a message by matching an advertisement to the message and identifying a place in the message to insert the advertisement. For textual messages, statistical analysis of individual sentences is performed to determine where it would be most natural to insert an advertisement. Statistical rules of grammar derived from a language model may be used choose a natural and grammatical place in the sentence for inserting the advertisement. Insertion of the advertisement creates a modified sentence without degrading a meaning of the original sentence, yet also includes the advertisement as a part of a new sentence.
    • 描述了用于生成文本嵌入式广告的计算机程序产品,设备和方法。 嵌入式广告通过将广告与消息进行匹配来隐藏或嵌入到消息中,并且识别消息中的位置以插入广告。 对于文本消息,执行单个句子的统计分析以确定插入广告最为自然的位置。 可以使用从语言模型导出的语法的统计规则,在句子中选择一个自然和语法的地方插入广告。 广告的插入创建一个修改后的句子,而不会降低原始句子的含义,而且还包括广告作为新句子的一部分。
    • 4. 发明申请
    • Automatic Video Recommendation
    • 自动视频推荐
    • US20090006368A1
    • 2009-01-01
    • US11771219
    • 2007-06-29
    • Tao MeiXian-Sheng HuaBo YangLinjun YangShipeng Li
    • Tao MeiXian-Sheng HuaBo YangLinjun YangShipeng Li
    • G06F17/30G06F3/00
    • H04N7/17318G06F16/735G06F16/78G06F16/7844G06F16/7847H04N21/466H04N21/4667H04N21/472
    • Automatic video recommendation is described. The recommendation does not require an existing user profile. The source videos are directly compared to a user selected video to determine relevance, which is then used as a basis for video recommendation. The comparison is performed with respect to a weighted feature set including at least one content-based feature, such as a visual feature, an aural feature and a content-derived textural feature. Multimodal implementation including multimodal features (e.g., visual, aural and textural) extracted from the videos is used for more reliable relevance ranking. One embodiment uses an indirect textural feature generated by automatic text categorization based on a set of predefined category hierarchy. Another embodiment uses self-learning based on user click-through history to improve relevance ranking.
    • 描述了自动视频推荐。 该建议不需要现有的用户配置文件。 源视频直接与用户选择的视频进行比较,以确定相关性,然后将其用作视频推荐的基础。 相对于包括至少一个基于内容的特征(例如视觉特征,听觉特征和内容导出的纹理特征)的加权特征集执行比较。 使用从视频提取的包括多模态特征(例如,视觉,听觉和纹理)的多模实现用于更可靠的相关性排名。 一个实施例使用基于一组预定义类别层次的自动文本分类生成的间接纹理特征。 另一个实施例使用基于用户点击历史的自学习来提高相关性排名。
    • 8. 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. 发明授权
    • Searching for images by video
    • 通过视频搜索图像
    • US09443011B2
    • 2016-09-13
    • US13110708
    • 2011-05-18
    • Linjun YangXian-Sheng HuaYang Cai
    • Linjun YangXian-Sheng HuaYang Cai
    • G06K9/46G06F17/30
    • G06K9/4676G06F17/30796G06F17/30799G06K9/00671G06K9/00744G06K9/38G06K9/4642G06K9/4671G06K9/623
    • Techniques describe submitting a video clip as a query by a user. A process retrieves images and information associated with the images in response to the query. The process decomposes the video clip into a sequence of frames to extract the features in a frame and to quantize the extracted features into descriptive words. The process further tracks the extracted features as points in the frame, a first set of points to correspond to a second set of points in consecutive frames to construct a sequence of points. Then the process identifies the points that satisfy criteria of being stable points and being centrally located in the frame to represent the video clip as a bag of descriptive words for searching for images and information related to the video clip.
    • 技术描述提交视频剪辑作为用户的查询。 响应于查询,进程检索与图像相关联的图像和信息。 该过程将视频剪辑分解成帧序列以提取帧中的特征并将提取的特征量化为描述性词。 该过程进一步跟踪提取的特征作为帧中的点,第一组点对应于连续帧中的第二组点以构成点序列。 然后,该过程识别满足稳定点的标准并且位于帧中心的点以将视频剪辑表示为用于搜索与视频剪辑相关的图像和信息的描述词的一袋。