公开(公告)号：US20130226693A1

公开(公告)日：2013-08-29

申请号：US13407762

申请日：2012-02-29

Applicant: Tao Qin ,  Tie-Yan Liu ,  Wei-Ying Ma

Inventor： Tao Qin ,  Tie-Yan Liu ,  Wei-Ying Ma

IPC: G06Q10/04 ,  G06Q30/02

CPC classification number: G06Q10/04 ,  G06Q30/02

Abstract: Functionality is described herein for allocating group-buying deals in a group-buying service. In certain implementations, the functionality operates by receiving deal information from deal-providing entities (such as merchants). The deal information describes plural deals. The functionality then assigns a number of impressions to each deal so as to maximize revenue provided to an entity which administers the group-buying service. This yields allocation information. The functionality then presents deals to users in accordance with the allocation information. For example, if the allocated number of impressions for a certain deal is x, then the functionality will provide x opportunities for users to select this deal.

Abstract translation: 本文描述了功能性，用于在集体购买服务中分配组购买交易。 在某些实现中，功能通过从交易提供实体（诸如商家）接收交易信息来进行操作。 交易信息描述多个交易。 然后，功能会为每个交易分配多个展示次数，以便最大限度地提供给管理群购服务的实体的收入。 这产生分配信息。 然后，该功能根据分配信息向用户呈现交易。 例如，如果某个交易的分配的展示次数为x，则功能将为用户提供选择此交易的机会。

公开(公告)号：US20130097011A1

公开(公告)日：2013-04-18

申请号：US13273924

申请日：2011-10-14

Applicant: Taifeng Wang ,  Tie-Yan Liu ,  Bin Gao ,  Tao Qin

Inventor： Taifeng Wang ,  Tie-Yan Liu ,  Bin Gao ,  Tao Qin

IPC: G06Q30/02

CPC classification number: G06Q30/02

Abstract: An advertisement perception predictor may forecast the effectiveness of an online advertisement in a web page by predicting whether the online advertisement may be perceived by a consumer. The advertisement perception predictor may use a perception model that is trained for determining perception probability values of online advertisements. The perception model may be applied to an online advertisement to determine a perception probability value for the online advertisement. The perception probability value may indicate the likelihood that a consumer is likely to view the online advertisement.

Abstract translation: 广告感知预测器可以通过预测在线广告是否可被消费者感知来预测网页中的在线广告的有效性。 广告感知预测器可以使用被训练用于确定在线广告的感知概率值的感知模型。 感知模型可以应用于在线广告以确定在线广告的感知概率值。 感知概率值可以指示消费者可能查看在线广告的可能性。

公开(公告)号：US20120271821A1

公开(公告)日：2012-10-25

申请号：US13090848

申请日：2011-04-20

Applicant: Tao Qin ,  Tie-Yan Liu ,  Xiubo Geng

Inventor： Tao Qin ,  Tie-Yan Liu ,  Xiubo Geng

IPC: G06F17/30

CPC classification number: G06F16/3346

Abstract: The relevance of an object, such as a document resulting from a query, may be determined automatically. A graphical model-based technique is applied to determine the relevance of the object. The graphical model may represent relationships between actual and observed labels for the object, based on features of the object. The graphical model may take into account an assumption of noisy training data by modeling the noise.

Abstract translation: 可以自动确定对象（例如由查询产生的文档）的相关性。 应用基于图形模型的技术来确定对象的相关性。 图形模型可以基于对象的特征来表示对象的实际标签和观察标签之间的关系。 图形模型可以通过对噪声建模来考虑噪声训练数据的假设。

公开(公告)号：US07853599B2

公开(公告)日：2010-12-14

申请号：US12017288

申请日：2008-01-21

Applicant: Tie-Yan Liu ,  Geng Xiubo ,  Tao Qin ,  Hang Li

Inventor： Tie-Yan Liu ,  Geng Xiubo ,  Tao Qin ,  Hang Li

IPC: G06F17/30

CPC classification number: G06F17/30675

Abstract: This disclosure describes various exemplary methods, computer program products, and systems for selecting features for ranking in information retrieval. This disclosure describes calculating importance scores for features, measuring similarity scores between two features, selecting features that maximizes total importance scores of the features and minimizes total similarity scores between the features. Also, the disclosure includes selecting features for ranking that solves an optimization problem. Thus, this disclosure identifies relevant features by removing noisy and redundant features and speeds up a process of model training.

Abstract translation: 本公开描述了各种示例性方法，计算机程序产品和用于选择用于在信息检索中排名的特征的系统。 该公开内容描述了计算特征的重要度得分，测量两个特征之间的相似性得分，选择使特征的总重要度得分最大化的特征并使特征之间的总相似性得分最小化的特征。 此外，本公开包括选择解决优化问题的排名特征。 因此，本公开通过去除噪声和冗余特征并加速模型训练的过程来识别相关特征。

公开(公告)号：US20070214116A1

公开(公告)日：2007-09-13

申请号：US11375612

申请日：2006-03-13

Applicant: Tie-Yan Liu ,  Tao Qin ,  Wei-Ying Ma

Inventor： Tie-Yan Liu ,  Tao Qin ,  Wei-Ying Ma

IPC: G06F17/30

CPC classification number: G06F17/30864 ,  Y10S707/99935 ,  Y10S707/99936

Abstract: A method and system for generating a search result for a query of hierarchically organized documents based on retrieval of subtrees that are key resources for topic distillation is provided. The retrieval system may identify documents relevant to a query using conventional searching techniques. The retrieval system then calculates a subtree feature for subtrees that have an identified document as their root. After the retrieval system calculates the subtree feature for the subtrees, the retrieval system may generate a subtree relevance score for each subtree based on its subtree feature. The retrieval system may then order the identified documents based on their corresponding subtree relevances.

Abstract translation: 提供了一种用于基于检索作为主题蒸馏的关键资源的子树来生成用于分层组织的文档的查询的搜索结果的方法和系统。 检索系统可以使用传统的搜索技术来识别与查询相关的文档。 检索系统然后计算具有识别的文档作为其根的子树的子树特征。 在检索系统计算子树的子树特征之后，检索系统可以基于其子树特征为每个子树生成子树相关性分数。 然后，检索系统可以基于它们相应的子树相关性来排序所识别的文档。

公开(公告)号：US20130246167A1

公开(公告)日：2013-09-19

申请号：US13421626

申请日：2012-03-15

Applicant: Tao Qin ,  Tie-Yan Liu ,  Wenkui Ding ,  Wei-Ying Ma ,  Hsiao-Wuen Hon

Inventor： Tao Qin ,  Tie-Yan Liu ,  Wenkui Ding ,  Wei-Ying Ma ,  Hsiao-Wuen Hon

IPC: G06Q30/02

CPC classification number: G06Q30/0256

Abstract: According to a cost-per-action advertising model, advertisers submit ads with cost-per-action bids. Ad auctions are conducted and winning ads are returned with contextually relevant search results. Each time a winning ad is selected by a user, resulting in the user being redirected to a website associated with the advertiser, a selected impression and a price is recorded for the winning ad. Periodically, an advertiser submits a report indicating a number of actions attributed to the ads that have occurred through the advertiser website. The advertiser is then charged a fee for each reported action based on the recorded prices for the winning ads and based on the number of selected impressions recorded for the winning ads.

Abstract translation: 根据每次操作费用广告模式，广告客户会按照每次操作费用出价提交广告。 进行广告拍卖，并返回具有内容相关搜索结果的获胜广告。 每当用户选择获胜广告时，导致用户被重定向到与广告商相关联的网站，则为获胜广告记录所选择的展示和价格。 定期地，广告客户会提交一份报告，指示通过广告客户网站发生的广告归因的一些操作。 然后，根据获胜广告的记录价格并根据为获胜广告记录的所选曝光次数，为每个报告的动作收取费用。

公开(公告)号：US20130097027A1

公开(公告)日：2013-04-18

申请号：US13272844

申请日：2011-10-13

Applicant: Taifeng Wang ,  Tie-Yan Liu ,  Bin Gao ,  Tao Qin

Inventor： Taifeng Wang ,  Tie-Yan Liu ,  Bin Gao ,  Tao Qin

IPC: G06Q30/02

CPC classification number: G06Q30/02

Abstract: A task guidance tool that displays instructional steps and associated advertisements may facilitate the accomplishment of a task by users who are otherwise unfamiliar with the task. The task guidance tool may be developed from input data mined from various sources. The task guidance tool may display a series of step pages in which each step page include instructions for accomplishing a corresponding step of the task. Further, one or more step pages of the task guidance tool may be provided with selected advertisements that are displayed with the step instructions.

Abstract translation: 显示教学步骤和相关联广告的任务指导工具可以促进由不熟悉任务的用户完成任务。 任务指导工具可以从从各种来源挖掘的输入数据中开发。 任务指导工具可以显示一系列步骤页面，其中每个步骤页面包括用于完成任务的相应步骤的指令。 此外，可以为任务指导工具的一个或多个步骤页面提供与步骤指令一起显示的所选择的广告。

公开(公告)号：US07890502B2

公开(公告)日：2011-02-15

申请号：US11273715

申请日：2005-11-14

Applicant: Tie-Yan Liu ,  Wei-Ying Ma ,  Tao Qin

Inventor： Tie-Yan Liu ,  Wei-Ying Ma ,  Tao Qin

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30864 ,  Y10S707/956

Abstract: A method and system for determining the contribution of a document within a hierarchy of documents based on the contribution of descendant documents is provided. The contribution system provides a hierarchy of documents that specifies the ancestor/descendant relations between documents. For each document of a hierarchy, the contribution system determines the contribution of each document factoring in the contribution of descendant documents. The contribution may be the relevance of a document to a topic, a feature of a document, and so on.

Abstract translation: 提供了一种用于基于后代文档的贡献来确定文档层级内的文档的贡献的方法和系统。 贡献系统提供了指定文档之间的祖先/后裔关系的文档层次结构。 对于层次结构的每个文档，供款系统确定每个文件保理在后代文件的贡献中的贡献。 贡献可能是文档与主题的相关性，文档的特征等等。

公开(公告)号：US20070233679A1

公开(公告)日：2007-10-04

申请号：US11278508

申请日：2006-04-03

Applicant: Tie-Yan Liu ,  Tao Qin ,  Wei-Ying Ma

Inventor： Tie-Yan Liu ,  Tao Qin ,  Wei-Ying Ma

IPC: G06F7/00

CPC classification number: G06F16/337 ,  G06F16/9535

Abstract: A method and system for learning a ranking function that uses a normalized, query-level error function is provided. A ranking system learns a ranking function using training data that includes, for each query, the corresponding documents and, for each document, its relevance to the corresponding query. The ranking system uses an error calculation algorithm that calculates an error between the actual relevances and the calculated relevances for the documents of each query. The ranking system normalizes the errors so that the total errors for each query will be weighted equally. The ranking system then uses the normalized error to learn a ranking function that works well for both queries with many documents in their search results and queries with few documents in their search results.

Abstract translation: 提供了一种用于学习使用归一化查询级错误函数的排序函数的方法和系统。 排名系统使用培训数据来学习排名功能，训练数据包括每个查询对应的文档，并为每个文档包含与相应查询的相关性。 排名系统使用错误计算算法来计算每个查询的文档的实际相关性和计算的相关性之间的误差。 排序系统对错误进行归一化，使每个查询的总错误平均加权。 排名系统然后使用归一化误差来学习排序函数，对于在其搜索结果中具有许多文档的查询以及在其搜索结果中具有少量文档的查询而言，该排序函数工作良好。

公开(公告)号：US08612453B2

公开(公告)日：2013-12-17

申请号：US12505436

申请日：2009-07-17

Applicant: Tie-Yan Liu ,  Tao Qin ,  Wei-Ying Ma

Inventor： Tie-Yan Liu ,  Tao Qin ,  Wei-Ying Ma

IPC: G06F7/00

CPC classification number: G06F17/30864 ,  Y10S707/99935 ,  Y10S707/99936

Abstract: A method and system for generating a search result for a query of hierarchically organized documents based on retrieval of subtrees that are key resources for topic distillation is provided. The retrieval system may identify documents relevant to a query using conventional searching techniques. The retrieval system then calculates a subtree feature for subtrees that have an identified document as their root. After the retrieval system calculates the subtree feature for the subtrees, the retrieval system may generate a subtree relevance score for each subtree based on its subtree feature. The retrieval system may then order the identified documents based on their corresponding subtree relevances.