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    • 1. 发明授权
    • Interactive framework for name disambiguation
    • 互动框架的名称消歧
    • US08538898B2
    • 2013-09-17
    • US13118404
    • 2011-05-28
    • Zhengdong LuZaiqing NieGang LuoYong CaoJi-Rong WenWei-Ying Ma
    • Zhengdong LuZaiqing NieGang LuoYong CaoJi-Rong WenWei-Ying Ma
    • G06N5/00
    • G06N99/005G06F17/30616
    • A “Name Disambiguator” provides various techniques for implementing an interactive framework for resolving or disambiguating entity names (associated with objects such as publications) for entity searches where two or more same or similar names may refer to different entities. More specifically, the Name Disambiguator uses a combination of user input and automatic models to address the disambiguation problem. In various embodiments, the Name Disambiguator uses a two part process, including: 1) a global SVM trained from large sets of documents or objects in a simulated interactive mode, and 2) further personalization of local SVM models (associated with individual names or groups of names such as, for example, a group of coauthors) derived from the global SVM model. The result of this process is that large sets of documents or objects are rapidly and accurately condensed or clustered into ordered sets by that are organized by entity names.
    • “名称歧义者”提供了各种技术,用于实现用于解析或消除实体名称(与诸如出版物的对象相关联)的交互式框架,用于实体搜索,其中两个或多个相同或相似的名称可以指代不同的实体。 更具体地说,名称消歧器使用用户输入和自动模型的组合来解决消歧问题。 在各种实施例中,名称消歧器使用两部分过程,包括:1)以模拟交互模式从大量文档或对象训练的全局SVM,以及2)本地SVM模型的进一步个性化(与个体名称或组相关联 来自全球SVM模型的名称,例如一组合作者。 这个过程的结果是,大量的文档或对象可以通过按实体名称组织的快速,准确的浓缩或聚类成有序集。
    • 2. 发明授权
    • Hierarchical conditional random fields for web extraction
    • Web提取的分层条件随机字段
    • US07720830B2
    • 2010-05-18
    • US11461400
    • 2006-07-31
    • Ji-Rong WenWei-Ying MaZaiqing NieJun Zhu
    • Ji-Rong WenWei-Ying MaZaiqing NieJun Zhu
    • G06F7/00G06F17/30G06F17/00G06F15/173
    • G06F17/3089G06F17/30994
    • A method and system for labeling object information of an information page is provided. A labeling system identifies an object record of an information page based on the labeling of object elements within an object record and labels object elements based on the identification of an object record that contains the object elements. To identify the records and label the elements, the labeling system generates a hierarchical representation of blocks of an information page. The labeling system identifies records and elements within the records by propagating probability-related information of record labels and element labels through the hierarchy of the blocks. The labeling system generates a feature vector for each block to represent the block and calculates a probability of a label for a block being correct based on a score derived from the feature vectors associated with related blocks. The labeling system searches for the labeling of records and elements that has the highest probability of being correct.
    • 提供了一种用于标记信息页面的对象信息的方法和系统。 标签系统基于对象记录中的对象元素的标签来识别信息页面的对象记录,并且基于包含对象元素的对象记录的标识来标记对象元素。 为了识别记录并标记元素,标签系统生成信息页的块的分层表示。 标签系统通过块的层次传播记录标签和元素标签的概率相关信息来识别记录中的记录和元素。 标签系统为每个块生成特征向量以表示块,并且基于从与相关块相关联的特征向量导出的分数来计算块正确的标签的概率。 标签系统搜索具有最高准确概率的记录和元素的标签。
    • 3. 发明授权
    • Information classification paradigm
    • 信息分类范式
    • US07529748B2
    • 2009-05-05
    • US11276818
    • 2006-03-15
    • Ji-Rong WenYan-Feng SunWei-Ying MaZaiqing NieRenkuan Jiang
    • Ji-Rong WenYan-Feng SunWei-Ying MaZaiqing NieRenkuan Jiang
    • G06F17/30
    • G06F17/30707Y10S707/99933Y10S707/99937
    • A mechanism to classify source documents into one of two categories, either likely to contain desired information or unlikely to contain desired information. Generally some form of rules based classification in conjunction with deeper analysis using advanced techniques on difficult cases is utilized. The rules based classification is generally good for eliminating cases from further consideration and for identifying documents of interest based on generally discernable relationships between data or based on the presence or absence of data. The deeper analysis is used to uncover more complex relationships between data that may identify documents of interest. Portions of the process may use the entire document while other portions of the process may use only a portion of the document.
    • 将源文档分类为两个类别之一的机制,可能包含所需信息或不太可能包含所需信息。 通常使用某种形式的基于规则的分类,结合使用先进技术在困难案例上进行更深入的分析。 基于规则的分类通常对于消除进一步考虑的情况以及基于数据之间的一般可辨别的关系或基于数据的存在或不存在来识别感兴趣的文档是有益的。 更深入的分析用于发现可能识别感兴趣文档的数据之间更复杂的关系。 过程的一部分可以使用整个文档,而进程的其他部分可以仅使用文档的一部分。
    • 8. 发明授权
    • Web-scale entity summarization
    • 网络规模实体总结
    • US08229960B2
    • 2012-07-24
    • US12570023
    • 2009-09-30
    • Zaiqing NieJi-Rong WenLiu Yang
    • Zaiqing NieJi-Rong WenLiu Yang
    • G06F17/00
    • G06F17/30867
    • Described is a summarizing a web entity (e.g., a person, place, product or so forth) based upon the entity's appearance in web documents (e.g., on the order of hundreds of millions or billions of webpages). Webpages are separated into blocks, which are then processed according to various features to filter the number of blocks to further process, and rank the most relevant blocks with respect to the entity that remain. A redundancy removal mechanism removes redundant blocks, leaving a set of remaining blocks that are used to provide a summary of information that is relevant to the entity.
    • 描述了基于实体在web文档中的出现(例如,数亿或数十亿个网页的数量级)来汇总web实体(例如,人,地点,产品等)。 网页被分成块,然后根据各种特征来处理块以过滤块的数量以进一步处理,并且相对于保留的实体排列最相关的块。 冗余删除机制去除冗余块,留下一组用于提供与该实体相关的信息摘要的剩余块。
    • 9. 发明授权
    • Automatic detection of online commercial intention
    • 自动检测在线商业意图
    • US07831685B2
    • 2010-11-09
    • US11300748
    • 2005-12-14
    • Honghua DaiLee WangYing LiZaiqing NieJi-Rong WenLingzhi Zhao
    • Honghua DaiLee WangYing LiZaiqing NieJi-Rong WenLingzhi Zhao
    • G06F15/16G06Q30/00
    • G06Q30/02
    • Features extracted from network browser pages and/or network search queries are leveraged to facilitate in detecting a user's browsing and/or searching intent. Machine learning classifiers constructed from these features automatically detect a user's online commercial intention (OCI). A user's intention can be commercial or non-commercial, with commercial intentions being informational or transactional. In one instance, an OCI ranking mechanism is employed with a search engine to facilitate in providing search results that are ranked according to a user's intention. This also provides a means to match purchasing advertisements with potential customers who are more than likely ready to make a purchase (transactional stage). Additionally, informational advertisements can be matched to users who are researching a potential purchase (informational stage).
    • 从网络浏览器页面和/或网络搜索查询中提取的特征被利用以便于检测用户的浏览和/或搜索意图。 从这些功能构建的机器学习分类器自动检测用户的在线商业意图(OCI)。 用户的意图可以是商业的或非商业的,商业意图是信息或交易的。 在一种情况下,使用OCI排名机制与搜索引擎,以便于提供根据用户意图进行排名的搜索结果。 这也提供了一种方法来将购买广告与潜在客户相匹配,潜在客户可能准备进行购买(交易阶段)。 此外,信息广告可以与正在研究潜在购买(信息阶段)的用户匹配。