公开(公告)号：US07813561B2

公开(公告)日：2010-10-12

申请号：US11464410

申请日：2006-08-14

申请人： Menglei Jia ,  Hua Li ,  Xing Xie ,  Zheng Chen ,  Wei-Ying Ma

发明人： Menglei Jia ,  Hua Li ,  Xing Xie ,  Zheng Chen ,  Wei-Ying Ma

IPC分类号： G06K9/62

CPC分类号： G06K9/4671 ,  G06F17/30247

摘要： A system for automatically classifying an object of a target image is provided. A classification system provides a collection of classified images along with a classification of the dominant object of the image. The classification system attempts to classify the object of a target image based on similarity of the target image to the classified images. To classify a target image, the classification system identifies the classified images of the collection that are most similar to the target image based on similarity between salient points of the target image and the classified images. The classification system selects a classification associated with the classified images that are most similar to the target image as a classification for the object of the target image.

摘要翻译： 提供了一种用于自动分类目标图像的对象的系统。 分类系统提供分类图像的集合以及图像的主要对象的分类。 分类系统尝试基于目标图像与分类图像的相似性对目标图像的对象进行分类。 为了对目标图像进行分类，分类系统基于目标图像的突出点与分类图像之间的相似度来识别与目标图像最相似的集合的分类图像。 分类系统选择与目标图像最相似的分类图像相关联的分类作为目标图像的对象的分类。

公开(公告)号：US20080037877A1

公开(公告)日：2008-02-14

申请号：US11464410

申请日：2006-08-14

申请人： Menglei Jia ,  Hua Li ,  Xing Xie ,  Zheng Chen ,  Wei-Ying Ma

发明人： Menglei Jia ,  Hua Li ,  Xing Xie ,  Zheng Chen ,  Wei-Ying Ma

IPC分类号： G06K9/62

CPC分类号： G06K9/4671 ,  G06F17/30247

摘要： A system for automatically classifying an object of a target image is provided. A classification system provides a collection of classified images along with a classification of the dominant object of the image. The classification system attempts to classify the object of a target image based on similarity of the target image to the classified images. To classify a target image, the classification system identifies the classified images of the collection that are most similar to the target image based on similarity between salient points of the target image and the classified images. The classification system selects a classification associated with the classified images that are most similar to the target image as a classification for the object of the target image.

摘要翻译： 提供了一种用于自动分类目标图像的对象的系统。 分类系统提供分类图像的集合以及图像的主要对象的分类。 分类系统尝试基于目标图像与分类图像的相似性对目标图像的对象进行分类。 为了对目标图像进行分类，分类系统基于目标图像的突出点与分类图像之间的相似度来识别与目标图像最相似的集合的分类图像。 分类系统选择与目标图像最相似的分类图像相关联的分类作为目标图像的对象的分类。

公开(公告)号：US08090709B2

公开(公告)日：2012-01-03

申请号：US11770307

申请日：2007-06-28

申请人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

发明人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

IPC分类号： G06F17/30

CPC分类号： G06Q30/02

摘要： Representing queries and determining similarity of queries based on an autoregressive integrated moving average (“ARIMA”) model is provided. A query analysis system represents each query by its ARIMA coefficients. The query analysis system may estimate the frequency information for a desired past or future interval based on frequency information for some initial intervals. The query analysis system may also determine the similarity of a pair of queries based on the similarity of their ARIMA coefficients. The query analysis system may use various metrics, such as a correlation metric, to determine the similarity of the ARIMA coefficients.

摘要翻译： 提供了基于自回归综合移动平均（“ARIMA”）模型的查询和确定查询的相似性。 查询分析系统通过其ARIMA系数表示每个查询。 查询分析系统可以基于一些初始间隔的频率信息来估计期望的过去或将来间隔的频率信息。 查询分析系统还可以基于它们的ARIMA系数的相似度来确定一对查询的相似性。 查询分析系统可以使用诸如相关度量的各种度量来确定ARIMA系数的相似性。

公开(公告)号：US07685100B2

公开(公告)日：2010-03-23

申请号：US11770462

申请日：2007-06-28

申请人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

发明人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

IPC分类号： G06F17/30

CPC分类号： G06Q30/02

摘要： Techniques for analyzing and modeling the frequency of queries are provided by a query analysis system. A query analysis system analyzes frequencies of a query over time to determine whether the query is time-dependent or time-independent. The query analysis system forecasts the frequency of time-dependent queries based on their periodicities. The query analysis system forecasts the frequency of time-independent queries based on causal relationships with other queries. To forecast the frequency of time-independent queries, the query analysis system analyzes the frequency of a query over time to identify significant increases in the frequency, which are referred to as “query events” or “events.” The query analysis system forecasts frequencies of time-independent queries based on queries with events that tend to causally precede events of the query to be forecasted.

摘要翻译： 用于分析和建模查询频率的技术由查询分析系统提供。 查询分析系统分析查询的频率，以确定查询是时间依赖还是时间无关。 查询分析系统根据其周期性预测与时间相关的查询的频率。 查询分析系统根据与其他查询的因果关系预测与时间无关的查询的频率。 为了预测时间无关查询的频率，查询分析系统随时间分析查询的频率，以识别频率的显着增加，这被称为“查询事件”或“事件”。查询分析系统预测频率 基于具有事件倾向于在要预测的查询的事件之前的查询的与时间无关的查询。

公开(公告)号：US20090327320A1

公开(公告)日：2009-12-31

申请号：US12146481

申请日：2008-06-26

申请人： Jun Yan ,  Ning Liu ,  Lei Ji ,  Zheng Chen ,  Jian Wang

发明人： Jun Yan ,  Ning Liu ,  Lei Ji ,  Zheng Chen ,  Jian Wang

IPC分类号： G06F17/30

CPC分类号： G06F17/30705

摘要： A method for merging really simple syndication (RSS) feeds. Stories containing one or more terms may be merged into one or more clusters based on one or more links between the stories. A cluster frequency with which the terms occur in each cluster may be determined. A diameter for each cluster may be determined. A cluster that is most similar to one of the clusters may be determined based on the cluster frequency. The most similar cluster with the one of the clusters may be determined based on each diameter, and each cluster frequency.

摘要翻译： 一种合并真正简单的联合（RSS）馈送的方法。 包含一个或多个术语的故事可以基于故事之间的一个或多个链接合并成一个或多个集群。 可以确定在每个簇中出现术语的聚类频率。 可以确定每个簇的直径。 可以基于群集频率来确定与簇之一最相似的群集。 可以基于每个直径和每个聚类频率来确定具有一个簇的最相似的簇。

公开(公告)号：US07529719B2

公开(公告)日：2009-05-05

申请号：US11378095

申请日：2006-03-17

申请人： Ning Liu ,  Benyu Zhang ,  Jun Yan ,  Zheng Chen ,  Hua-Jun Zeng ,  Jian Wang

发明人： Ning Liu ,  Benyu Zhang ,  Jun Yan ,  Zheng Chen ,  Hua-Jun Zeng ,  Jian Wang

IPC分类号： G06N5/00

CPC分类号： G06N5/02 ,  G06F17/30705

摘要： Computer-readable media having computer-executable instructions and apparatuses categorize documents or corpus of documents. A Tensor Space Model (TSM), which models the text by a higher-order tensor, represents a document or a corpus of documents. Supported by techniques of multilinear algebra, TSM provides a framework for analyzing the multifactor structures. TSM is further supported by operations and presented tools, such as the High-Order Singular Value Decomposition (HOSVD) for a reduction of the dimensions of the higher-order tensor. The dimensionally reduced tensor is compared with tensors that represent possible categories. Consequently, a category is selected for the document or corpus of documents. Experimental results on the dataset for 20 Newsgroups suggest that TSM is advantageous to a Vector Space Model (VSM) for text classification.

摘要翻译： 具有计算机可执行指令和设备的计算机可读介质将文档或语料库分类。 张量空间模型（TSM），其通过高阶张量对文本进行建模，表示文档或文档语料库。 由多线代数技术支持，TSM为多因素结构分析提供了框架。 TSM还受到操作和提出的工具的支持，例如用于降低高阶张量尺寸的高阶奇异值分解（HOSVD）。 将尺寸减小的张量与表示可能类别的张量进行比较。 因此，文档或文档的语料库选择一个类别。 20个新闻组的数据集的实验结果表明，TSM对于文本分类的向量空间模型（VSM）是有利的。

公开(公告)号：US07502785B2

公开(公告)日：2009-03-10

申请号：US11392761

申请日：2006-03-30

申请人： Zheng Chen ,  Lei Li ,  Chenxi Lin ,  Qiaoling Liu ,  Jian Wang ,  Benyu Zhang

发明人： Zheng Chen ,  Lei Li ,  Chenxi Lin ,  Qiaoling Liu ,  Jian Wang ,  Benyu Zhang

IPC分类号： G06F17/30

CPC分类号： G06F17/30616 ,  G06F17/30112 ,  G06F17/3012 ,  Y10S707/99933

摘要： Extraction of semantic information and the generation of semantic attributes allows for improved organization and management of data. Semantic attributes are automatically generated and eliminate the need for manual entry of attribute information. A semantic file network may further be constructed based on similarities between files that are based on the semantic attribute information. Semantic links representing a semantic relationship may be built between similar or relevant files. In addition, user operations and user operation patterns may also be considered in building the file network. Semantic attributes and information may further facilitate browsing the file systems as well as improve the accuracy and speed of queries.

摘要翻译： 语义信息的提取和语义属性的产生可以改善数据的组织和管理。 自动生成语义属性，无需手动输入属性信息。 还可以基于基于语义属性信息的文件之间的相似性来构建语义文件网络。 表示语义关系的语义链接可以在相似或相关文件之间建立。 此外，在构建文件网络时也可以考虑用户操作和用户操作模式。 语义属性和信息可以进一步促进文件系统的浏览以及提高查询的准确性和速度。

公开(公告)号：US20090006294A1

公开(公告)日：2009-01-01

申请号：US11770423

申请日：2007-06-28

申请人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

发明人： Ning Liu ,  Jun Yan ,  Benyu Zhang ,  Zheng Chen ,  Jian Wang

IPC分类号： G06N5/00

CPC分类号： G06F17/30864 ,  G06Q30/02

摘要： Techniques for analyzing and modeling the frequency of queries are provided by a query analysis system. A query analysis system analyzes frequencies of a query over time to determine whether the query is time-dependent or time-independent. The query analysis system forecasts the frequency of time-dependent queries based on their periodicities. The query analysis system forecasts the frequency of time-independent queries based on causal relationships with other queries. To forecast the frequency of time-independent queries, the query analysis system analyzes the frequency of a query over time to identify significant increases in the frequency, which are referred to as “query events” or “events.” The query analysis system forecasts frequencies of time-independent queries based on queries with events that tend to causally precede events of the query to be forecasted.

摘要翻译： 用于分析和建模查询频率的技术由查询分析系统提供。 查询分析系统分析查询的频率，以确定查询是时间依赖还是时间无关。 查询分析系统根据其周期性预测与时间相关的查询的频率。 查询分析系统根据与其他查询的因果关系预测与时间无关的查询的频率。 为了预测与时间无关的查询的频率，查询分析系统会随着时间的推移分析查询的频率，以确定频率的显着增加，这被称为“查询事件”或“事件”。 查询分析系统基于具有事件倾向于在要预测的查询的事件之前的查询来预测与时间无关的查询的频率。

公开(公告)号：US20080249762A1

公开(公告)日：2008-10-09

申请号：US11697112

申请日：2007-04-05

申请人： Jian Wang ,  Jian-Tao Sun ,  Shen Huang ,  Zheng Chen

发明人： Jian Wang ,  Jian-Tao Sun ,  Shen Huang ,  Zheng Chen

IPC分类号： G06F17/20

CPC分类号： G06F17/2785

摘要： A method and system is provided for classifying documents based on the subjectivity of the content of the documents using a part-of-speech analysis to help account for unseen words. A classification system trains a classifier using the parts of speech of training documents so that the classifier can classify unseen words based on the part of speech of the unseen word. The classification system then trains a part-of-speech model using the parts of speech of the n-grams of training data and labels of the training documents, and trains a term model using the term unigrams and labels. To classify a target document, the classification system applies the part-of-speech model to the part-of-speech n-grams of the target document and the term model to term n-grams of the target document.

摘要翻译： 提供了一种方法和系统，用于使用语音分析基于文档内容的主观性对文档进行分类，以帮助解释看不见的单词。 分类系统使用训练文档的部分语言训练分类器，以便分类器可以根据不可见词的部分语言对不可见的单词进行分类。 然后，分类系统使用训练数据的n-gram和训练文档的标签的词性训练一部分语音模型，并且使用术语单词和标签来训练术语模型。 为了对目标文件进行分类，分类系统将部分词汇模型应用于目标文档的词性n-gram和目标文档的术语模型至术语n-gram。

公开(公告)号：US20080208819A1

公开(公告)日：2008-08-28

申请号：US12038588

申请日：2008-02-27

申请人： Min Wang ,  Zheng Chen ,  Jian-Tao Sun ,  Shen Huang ,  Jian Wang

发明人： Min Wang ,  Zheng Chen ,  Jian-Tao Sun ,  Shen Huang ,  Jian Wang

IPC分类号： G06F17/30

CPC分类号： G06F17/30696 ,  G06F17/30643 ,  G06F17/30864

摘要： An exemplary computer implemented graphics-based Web search system includes a search input control and a results presentation control where the search input control is configured to receive user input to establish a relationship between a query and one or more information tags associated with search results provided by a search engine in response to the query and wherein the results presentation control is configured to re-order the search results in response to the relationship. Such a system allows a user to define and refine search intent and enhance the user's search experience. Various other exemplary systems, methods, devices, etc. are also disclosed.

摘要翻译： 示例性的计算机实现的基于图形的Web搜索系统包括搜索输入控制和结果呈现控制，其中搜索输入控件被配置为接收用户输入以建立查询与与由搜索结果提供的搜索结果相关联的一个或多个信息标签之间的关系 搜索引擎，其响应于所述查询，并且其中所述结果呈现控制被配置为响应于所述关系重新排序所述搜索结果。 这样的系统允许用户定义和优化搜索意图并增强用户的搜索体验。 还公开了各种其它示例性系统，方法，装置等。