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1. 发明申请

US20130191310A1 PREDICTION MODEL REFINEMENT FOR INFORMATION RETRIEVAL SYSTEM 审中-公开
标题翻译：信息检索系统的预测模型修订
公开(公告)号：US20130191310A1
公开(公告)日：2013-07-25
申请号：US13355576
申请日：2012-01-23
申请人： Ahmed Hassan Awadallah
发明人： Ahmed Hassan Awadallah
IPC分类号： G06F15/18
CPC分类号： G06F16/33 , G06N20/00
摘要： A learning system refines a prediction model that determines the effectiveness of a search engine in achieving a goal of a search. Search goal achievements are estimated for sequences of user actions in an unlabeled data set using the prediction model, which is based on a mixture model and values for parameters of the mixture model. The values of the parameters are redefined based at least on the search goal achievement estimates of the unlabeled set. The prediction model is stored in accordance with the mixture model and the redefined values.
摘要翻译：学习系统改进了一个预测模型，该模型决定了搜索引擎实现搜索目标的有效性。使用基于混合模型和混合模型参数值的预测模型，在未标记数据集中的用户行为序列估计搜索目标成绩。至少基于未标记集合的搜索目标成就估算值，重新定义参数的值。预测模型根据混合模型和重新定义的值进行存储。

2. 发明申请

US20100161591A1 SYSTEM AND METHOD OF GEO-BASED PREDICTION IN SEARCH RESULT SELECTION 有权
标题翻译：搜索结果选择中基于GEO的预测的系统和方法
公开(公告)号：US20100161591A1
公开(公告)日：2010-06-24
申请号：US12341327
申请日：2008-12-22
申请人： Rosie Jones , Fernando Diaz , Ahmed Hassan Awadallah
发明人： Rosie Jones , Fernando Diaz , Ahmed Hassan Awadallah
IPC分类号： G06F7/06 , G06F17/30
CPC分类号： G06F17/30241
摘要： A system and method is disclosed for determining a prediction measurement, or measure, using geo-spatial information which can be used to determine whether or not to include type of information in search results. The prediction measurement comprises a measure of the likelihood that an item of the type of information for which the prediction measure is determined will be selected, or clicked on, by a user, if the item of the type of information is included in the search result. Without limitation, one such information type is news.
摘要翻译：公开了一种用于确定使用地理空间信息的预测测量或测量的系统和方法，所述地理空间信息可用于确定是否在搜索结果中包括信息类型。预测测量包括如果信息类型的项目被包括在搜索结果中，则用户将选择或点击预测度量的信息类型的项目的可能性的度量。没有限制，一种这样的信息类型是新闻。

3. 发明授权

US08352466B2 System and method of geo-based prediction in search result selection 有权
标题翻译：搜索结果选择中基于地理预测的系统和方法
公开(公告)号：US08352466B2
公开(公告)日：2013-01-08
申请号：US12341327
申请日：2008-12-22
申请人： Rosie Jones , Fernando Diaz , Ahmed Hassan Awadallah
发明人： Rosie Jones , Fernando Diaz , Ahmed Hassan Awadallah
IPC分类号： G06F17/30
CPC分类号： G06F17/30241
摘要： A system and method is disclosed for determining a prediction measurement, or measure, using geo-spatial information which can be used to determine whether or not to include type of information in search results. The prediction measurement comprises a measure of the likelihood that an item of the type of information for which the prediction measure is determined will be selected, or clicked on, by a user, if the item of the type of information is included in the search result. Without limitation, one such information type is news.
摘要翻译：公开了一种用于确定使用地理空间信息的预测测量或测量的系统和方法，所述地理空间信息可用于确定是否在搜索结果中包括信息类型。预测测量包括如果信息类型的项目被包括在搜索结果中，则用户将选择或点击预测度量的信息类型的项目的可能性的度量。没有限制，一种这样的信息类型是新闻。

4. 发明授权

US10108704B2 Identifying dissatisfaction segments in connection with improving search engine performance 有权
公开(公告)号：US10108704B2
公开(公告)日：2018-10-23
申请号：US13604627
申请日：2012-09-06
申请人： Ahmed Hassan Awadallah , Yi-Min Wang , Ryen William White
发明人： Ahmed Hassan Awadallah , Yi-Min Wang , Ryen William White
IPC分类号： G06F17/30
摘要： Technologies pertaining to automatically identifying sets of query attribute values that are highly correlative with user dissatisfaction with a search engine are described. Dissatisfied queries are automatically identified through analysis of search logs, wherein a dissatisfied query is a query submitted to a search engine by a user, wherein the user was dissatisfied with search results provided by the search engine responsive to receipt of the query. Sets of query attribute values that are highly correlated with dissatisfied queries, and thus user dissatisfaction, are automatically identified based at least in part upon the identifying of the dissatisfied queries. Subsequent to identifying a set of query attribute values, a segment-specific ranker is learned that is configured to rank search results responsive to receipt of a query with the set of query attribute values, wherein the segment-specific ranker outperforms a general purpose ranker for queries having the set of query attribute values.

5. 发明授权

US09443028B2 Relevance estimation using a search satisfaction metric 有权
标题翻译：使用搜索满意度度量的相关度估计
公开(公告)号：US09443028B2
公开(公告)日：2016-09-13
申请号：US12965864
申请日：2010-12-11
申请人： Yang Song , Liwei He , Ahmed Hassan Awadallah
发明人： Yang Song , Liwei He , Ahmed Hassan Awadallah
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30882 , G06F17/30864
摘要： The subject disclosure is directed towards using a satisfaction model's prediction as to whether a user was satisfied or dissatisfied in satisfying a search goal to help estimate the relevance of a URL/document that was returned and clicked by the user. The clickthrough data for a search goal session is processed by either a utility model or a despair model based on whether the satisfaction model indicated that the search goal session ended with the user satisfied or dissatisfied, respectively. The utility model distributes a utility value to each clicked URL, while the despair model distributes a despair value to each clicked URL. The utility value and despair value of each query-URL pair may be used as corresponding feature data for learning a search ranker.
摘要翻译：主题公开涉及使用满意度模型对用户满足或不满意满足搜索目标以帮助估计用户返回和点击的URL /文档的相关性的预测。搜索目标会话的点击数据由实用新型或绝对模型基于满意度模型是否表示搜索目标会话分别以满足或不满意的方式结束来处理。实用新型将实用值分配给每个点击的URL，而绝望模型将绝望值分配给每个点击的URL。每个查询URL对的效用值和绝望值可以被用作学习搜索列表的相应特征数据。

6. 发明申请

US20140067783A1 IDENTIFYING DISSATISFACTION SEGMENTS IN CONNECTION WITH IMPROVING SEARCH ENGINE PERFORMANCE 审中-公开
标题翻译：识别与改进搜索引擎性能有关的不符合条款
公开(公告)号：US20140067783A1
公开(公告)日：2014-03-06
申请号：US13604627
申请日：2012-09-06
申请人： Ahmed Hassan Awadallah , Yi-Min Wang , Ryen William White
发明人： Ahmed Hassan Awadallah , Yi-Min Wang , Ryen William White
IPC分类号： G06F17/30
CPC分类号： G06F17/30699 , G06F17/30657
摘要： Technologies pertaining to automatically identifying sets of query attribute values that are highly correlative with user dissatisfaction with a search engine are described. Dissatisfied queries are automatically identified through analysis of search logs, wherein a dissatisfied query is a query submitted to a search engine by a user, wherein the user was dissatisfied with search results provided by the search engine responsive to receipt of the query. Sets of query attribute values that are highly correlated with dissatisfied queries, and thus user dissatisfaction, are automatically identified based at least in part upon the identifying of the dissatisfied queries. Subsequent to identifying a set of query attribute values, a segment-specific ranker is learned that is configured to rank search results responsive to receipt of a query with the set of query attribute values, wherein the segment-specific ranker outperforms a general purpose ranker for queries having the set of query attribute values.
摘要翻译：描述与自动识别与用户对搜索引擎不满意度高度相关的查询属性值集合的技术。通过分析搜索日志来自动识别不满意的查询，其中不满意的查询是由用户提交给搜索引擎的查询，其中用户对响应于接收查询的搜索引擎提供的搜索结果不满意。至少部分地基于不满意的查询的识别来自动识别与不满意的查询高度相关并且因此用户不满意的查询属性值的集合。在识别一组查询属性值之后，学习一个段特定的队员，其被配置为响应于使用该组查询属性值接收到查询来对搜索结果进行排序，其中，该段特定的队友优于通用目标，具有查询属性值集的查询。

7. 发明申请

US20120150854A1 Relevance Estimation using a Search Satisfaction Metric 有权
标题翻译：使用搜索满意度指标的相关性估计
公开(公告)号：US20120150854A1
公开(公告)日：2012-06-14
申请号：US12965864
申请日：2010-12-11
申请人： Yang Song , Liwei He , Ahmed Hassan Awadallah
发明人： Yang Song , Liwei He , Ahmed Hassan Awadallah
IPC分类号： G06F17/30
CPC分类号： G06F17/30882 , G06F17/30864
摘要： The subject disclosure is directed towards using a satisfaction model's prediction as to whether a user was satisfied or dissatisfied in satisfying a search goal to help estimate the relevance of a URL/document that was returned and clicked by the user. The clickthrough data for a search goal session is processed by either a utility model or a despair model based on whether the satisfaction model indicated that the search goal session ended with the user satisfied or dissatisfied, respectively. The utility model distributes a utility value to each clicked URL, while the despair model distributes a despair value to each clicked URL. The utility value and despair value of each query-URL pair may be used as corresponding feature data for learning a search ranker.
摘要翻译：主题公开涉及使用满意度模型对用户满足或不满意满足搜索目标以帮助估计用户返回和点击的URL /文档的相关性的预测。搜索目标会话的点击数据由实用新型或绝对模型基于满意度模型是否表示搜索目标会话分别以满足或不满意的方式结束来处理。实用新型将实用值分配给每个点击的URL，而绝望模型将绝望值分配给每个点击的URL。每个查询URL对的效用值和绝望值可以被用作学习搜索列表的相应特征数据。

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