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    • 24. 发明申请
    • System and methods for data analysis and trend prediction
    • 数据分析和趋势预测的系统和方法
    • US20060184464A1
    • 2006-08-17
    • US11127893
    • 2005-05-12
    • Belle TsengYi Wu
    • Belle TsengYi Wu
    • G06F15/18
    • G06N5/003G06F16/313
    • Systems and methods for data analysis and trend prediction. Multiple networks are combined for analysis to improve the accuracy of the evaluation by broadening the type of criteria considered. Relevant features are extracted from a dataset and at least one network is formed representing various relationships identified among the items contained in the dataset according to heuristics. Statistical analyses are applied to the relationships and the results output to a user via one or more reports to permit a user to evaluate each of the items in the dataset relative to each other. The trend of the relationships may be predicted based on the results of statistical analysis applied to the features over successive discrete time periods.
    • 数据分析和趋势预测的系统和方法。 组合多个网络进行分析,通过扩大考虑的标准类型来提高评估的准确性。 从数据集中提取相关特征,并根据启发式形成代表在数据集中包含的项目中识别的各种关系的至少一个网络。 统计分析应用于通过一个或多个报告向用户输出的关系和结果,以允许用户相对于彼此评估数据集中的每个项目。 可以基于在连续的离散时间段上应用于特征的统计分析的结果来预测关系的趋势。
    • 25. 发明申请
    • Method and apparatus for ontology-based classification of media content
    • 用于基于本体的媒体内容分类的方法和装置
    • US20060031217A1
    • 2006-02-09
    • US10910118
    • 2004-08-03
    • John SmithBelle TsengYi Wu
    • John SmithBelle TsengYi Wu
    • G06F17/30
    • G06K9/00711G06K9/6292Y10S707/99935Y10S707/99943
    • A method and apparatus for ontology-based classification of media content are provided. With the method and apparatus, initial confidence values of classifiers in a hierarchical classification structure are modified based on relationships between classifiers. A confidence value for a classifier is boosted by a boosting factor based on a correspondence between the confidence value and confidence values of ancestor classifiers in the hierarchical classification structure. A confidence value for a classifier is modified by a confusion factor based on a correspondence between the confidence value of the classifier and the confidence values of mutually exclusive classifiers in the hierarchical classification structure. In this way, a more accurate representation of the actual confidence that media content falls within the classification associated with the classifier is obtained. From this improved classification mechanism, indices for media content may be generated for use in accessing the media content at a later time.
    • 提供了一种用于基于本体的媒体内容分类的方法和装置。 利用该方法和装置,基于分类器之间的关系来修改分层分类结构中分类器的初始置信度值。 基于分级分类结构中的祖先分类器的置信度值和置信度值之间的对应关系,通过增强因子来提高分类器的置信度值。 基于分类器的置信度值与层次分类结构中互斥分类器的置信度值之间的对应关系,通过混淆因子修改分类器的置信度值。 以这种方式,获得媒体内容落入与分类器相关联的分类内的实际置信度的更准确的表示。 根据该改进的分类机制,可以生成用于媒体内容的索引以用于在稍后的时间访问媒体内容。
    • 28. 发明申请
    • METHODS AND SYSTEMS FOR UTILIZING CONTENT, DYNAMIC PATTERNS, AND/OR RELATIONAL INFORMATION FOR DATA ANALYSIS
    • 利用内容,动态模式和/或数据分析的关系信息的方法和系统
    • US20070118498A1
    • 2007-05-24
    • US11562810
    • 2006-11-22
    • Xiaodan SongBelle Tseng
    • Xiaodan SongBelle Tseng
    • G06F17/30
    • G06F17/30702G06F17/30716G06Q30/0633
    • The present invention is directed generally to providing systems and methods for data analysis. More specifically, embodiments may provide system(s) and method(s) including dynamic user modeling techniques to capture the relational and dynamic patterns of information content and/or users' or entities' interests. Various embodiments may include system(s) and method(s) that are based on, for example, the past history of content semantics, temporal changes, and/or user community relationship. Various embodiments may include modeling and/or analysis of the dynamic nature of an item of interest's value to a user(s)/entity(ies) over time. The dynamic factors may be consider in any manner, such as, individually or combined, sequentially or simultaneously, etc. Further, some embodiments may include, for example, system(s) and method(s) relating to analyzing data to capture user/entity interests and/or characteristics, consider content semantics and evolutionary information, and/or using community relationships of users/entities to thereby analyze information and provide dynamic conclusion(s) (e.g., recommendation(s)).
    • 本发明一般涉及提供用于数据分析的系统和方法。 更具体地,实施例可以提供包括动态用户建模技术的系统和方法,以捕获信息内容和/或用户或实体兴趣的关系和动态模式。 各种实施例可以包括基于例如内容语义,时间变化和/或用户社区关系的过去历史的系统和方法。 各种实施方案可以包括随着时间的推移,对用户/实体的兴趣物品的价值的动态性质的建模和/或分析。 动态因素可以以任何方式,例如,单独地或组合地顺序地或同时地等来考虑。此外,一些实施例可以包括例如与分析数据相关的系统和方法,以捕获用户/ 实体利益和/或特征,考虑内容语义和进化信息,和/或使用用户/实体的社区关系,从而分析信息并提供动态结论(例如推荐)。
    • 29. 发明申请
    • SYSTEMS AND METHODS FOR TREND EXTRACTION AND ANALYSIS OF DYNAMIC DATA
    • 用于趋势提取和动态数据分析的系统和方法
    • US20070100875A1
    • 2007-05-03
    • US11556091
    • 2006-11-02
    • Yun ChiBelle TsengJunichi Tatemura
    • Yun ChiBelle TsengJunichi Tatemura
    • G06F7/00
    • G06Q30/02
    • The invention is directed generally to providing methods and systems for trend extraction and analysis. Embodiments include methods and systems for trend extraction and analysis of information extracted from dynamically changing data included in computer systems and/or networks. Various exemplary embodiments are provided that may generate characteristic indicators for trend(s) and/or distribution(s) for one or more data sources by use of, for example, temporal indicators derived through analysis of the difference in contribution separate portions of the data to the whole data set being considered, contribution of individual sources, and/or the interaction of the separate portions of the data with one another. Some exemplary approaches may include the use of singular value decomposition (SVD) and higher-order singular value decomposition (HOSVD) data extraction and analysis techniques. One use of these techniques is in the analysis of the dynamic data contained in Weblogs and the blogosphere.
    • 本发明一般涉及提供用于趋势提取和分析的方法和系统。 实施例包括用于趋势提取和分析从包括在计算机系统和/或网络中的动态变化的数据提取的信息的方法和系统。 提供了各种示例性实施例,其可以通过使用例如通过分析贡献分离而导出的用于一个或多个数据源的趋势和/或分布的特征指标,分离部分的数据 被考虑的整个数据集,各个来源的贡献,和/或数据的分开的部分的相互作用。 一些示例性方法可以包括使用奇异值分解(SVD)和高阶奇异值分解(HOSVD)数据提取和分析技术。 这些技术的一个用途是分析博客和博客圈子中包含的动态数据。