专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

21. 发明授权

US07480667B2 System and method for using anchor text as training data for classifier-based search systems 有权
标题翻译：使用锚文本作为基于分类器的搜索系统的训练数据的系统和方法
公开(公告)号：US07480667B2
公开(公告)日：2009-01-20
申请号：US11023856
申请日：2004-12-24
申请人： Chen Harr , Adwait Ratnaparkhi , Sonja S. Knoll , Hsiao-Wuen Hon
发明人： Chen Harr , Adwait Ratnaparkhi , Sonja S. Knoll , Hsiao-Wuen Hon
IPC分类号： G06F17/30
CPC分类号： G06F17/30663 , G06F17/30705 , G06F17/30867 , Y10S707/99942 , Y10S707/99943
摘要： A computer implemented information retrieval system is provided. The system includes a user input configured to receive a user query relative to the corpus. A machine learning classifier is trained with a first set of training data comprising anchor text relative to at least some of the documents in the corpus. A processing unit is adapted to interact with the classifier to obtain search results relative to the query using the machine learning classifier. In some aspects, the classifier is also trained with a second set of training data. A method of integrating a new document into a corpus of documents is also provided. A method of training a machine learning classifier for retrieving documents from a corpus using two distinct types of training data is also provided.
摘要翻译：提供了一种计算机实现的信息检索系统。系统包括被配置为接收相对于语料库的用户查询的用户输入。用机器学习分类器训练第一组训练数据，其包括相对于语料库中的至少一些文档的锚文本。处理单元适于与分类器交互以获得相对于使用机器学习分类器的查询的搜索结果。在一些方面，分类器还训练有第二组训练数据。还提供了将新文档集成到文档语料库中的方法。还提供了一种使用两种不同类型的训练数据来训练用于从语料库检索文档的机器学习分类器的方法。

22. 发明授权

US07424469B2 System and method for blending the results of a classifier and a search engine 有权
标题翻译：用于混合分类器和搜索引擎结果的系统和方法
公开(公告)号：US07424469B2
公开(公告)日：2008-09-09
申请号：US10752901
申请日：2004-01-07
申请人： Adwait Ratnaparkhi
发明人： Adwait Ratnaparkhi
IPC分类号： G06F7/00
CPC分类号： G06F17/30687 , G06F17/30864 , Y10S707/99933 , Y10S707/99937
摘要： A method to produce a list of documents retrieved from a search engine, ranked according to their relevance to search terms, includes interleaving the lists resulting from two searches. The first search is one that occurs over documents where the list is ranked using a first probabilistic ranking algorithm. The second list is a list of documents obtained by searching over a query log of prior searches using the same search terms. The second list is ranked according to a second probabilistic algorithm. Interleaving of the two lists includes eliminating duplicate occurrences of documents and appending the remaining documents to the end of the interleaved list if the two lists of individual search results differ in length. The interleaved list may then be presented to a user for review.
摘要翻译：产生从搜索引擎检索的根据其与搜索词的相关性排列的文档的列表的方法包括交织由两次搜索产生的列表。第一个搜索是使用第一概率排序算法在列表排序的文档上发生的搜索。第二个列表是通过使用相同的搜索项搜索先前搜索的查询日志获得的文档的列表。第二列表根据第二概率算法进行排序。两个列表的交织包括消除重复出现的文档，并将剩余文档附加到交错列表的末尾，如果个别搜索结果的两个列表长度不同。然后可以将交错列表呈现给用户进行审查。

23. 发明授权

US07231375B2 Computer aided query to task mapping 失效
标题翻译：计算机辅助查询到任务映射
公开(公告)号：US07231375B2
公开(公告)日：2007-06-12
申请号：US10683807
申请日：2003-10-10
申请人： Adwait Ratnaparkhi , Robert John Ragno , Felipe Luis Naranjo , Boris Gorodnitsky
发明人： Adwait Ratnaparkhi , Robert John Ragno , Felipe Luis Naranjo , Boris Gorodnitsky
IPC分类号： G06F15/00
CPC分类号： G06F17/30722 , G06F17/30654 , G06F17/30675
摘要： An annotating system aids a user in mapping a large number of queries to tasks to obtain training data for training a search component. The annotating system includes a query log containing a large quantity of queries which have previously been submitted to a search engine. A task list containing a plurality of possible tasks is stored. A machine learning component processes the query log data and the task list data. For each of a plurality of query entries corresponding to the query log, the machine learning component suggests a best guess task for potential query-to-task mapping as a function of the training data. A graphical user interface generating component is configured to display the plurality of query entries in the query log in a manner which associates each of the displayed plurality of query entries with its corresponding suggested best guess task.
摘要翻译：注释系统帮助用户将大量查询映射到任务以获得用于训练搜索组件的训练数据。注释系统包括包含先前已提交到搜索引擎的大量查询的查询日志。存储包含多个可能任务的任务列表。机器学习组件处理查询日志数据和任务列表数据。对于与查询日志相对应的多个查询条目中的每一个，机器学习部件建议作为训练数据的函数的潜在查询到任务映射的最佳猜测任务。图形用户界面生成组件被配置为以将每个所显示的多个查询条目与其对应的建议最佳猜测任务相关联的方式在查询日志中显示多个查询条目。

24. 发明申请

US20060287980A1 Intelligent search results blending 审中-公开
标题翻译：智能搜索结果混合
公开(公告)号：US20060287980A1
公开(公告)日：2006-12-21
申请号：US11157599
申请日：2005-06-21
申请人： Jun Liu , Adwait Ratnaparkhi , Qi Yao , Sanjeev Katariya
发明人： Jun Liu , Adwait Ratnaparkhi , Qi Yao , Sanjeev Katariya
IPC分类号： G06F17/30
CPC分类号： G06F16/951
摘要： The subject invention relates to systems and methods that automatically combine or interleave received search results from across knowledge databases in a uniform and consistent manner. In one aspect, an automated search results blending system is provided. The system includes a search component that directs a query to at least two databases. A learning component is employed to rank or score search results that are received from the databases in response to the query. A blending component automatically interleaves or combines the results according to the rank in order to provide a consistent ranking system across differing knowledge sources and search tools.
摘要翻译：本发明涉及以统一和一致的方式自动地组合或交织来自跨知识数据库的接收的搜索结果的系统和方法。一方面，提供了一种自动搜索结果混合系统。该系统包括将查询引导至少两个数据库的搜索组件。采用学习组件对从数据库接收的响应于查询的搜索结果进行排名或评分。混合组件根据等级自动地交织或组合结果，以便在不同的知识源和搜索工具之间提供一致的排名系统。

25. 发明申请

US20060253428A1 Performant relevance improvements in search query results 有权
公开(公告)号：US20060253428A1
公开(公告)日：2006-11-09
申请号：US11123277
申请日：2005-05-06
申请人： Sanjeev Katariya , Qi Yao , Jun Liu , Adwait Ratnaparkhi , Bradley Green
发明人： Sanjeev Katariya , Qi Yao , Jun Liu , Adwait Ratnaparkhi , Bradley Green
IPC分类号： G06F17/30
CPC分类号： G06F17/30864 , Y10S707/99932 , Y10S707/99933
摘要： Property store information and an aggregation of a plurality of ranking mechanisms, including a learning mechanism, are leveraged to provide performant query results with increased user relevancy. The learning mechanism permits query feedback to be accepted to facilitate in optimizing user relevance. This mechanism can also be incorporated with traditional Information Retrieval (IR) components, each supplying independent ranking to a relevance aggregation function that determines relevancy at a high level. This precludes diminishing the value of query feedback that occurs when the data is fed into traditional IR algorithms. By allowing the query feedback to maintain its proper weighting and utilizing scope and bias capabilities of the property store information, relevance increases in a highly performant manner.

26. 发明申请

US20060143254A1 System and method for using anchor text as training data for classifier-based search systems 有权
公开(公告)号：US20060143254A1
公开(公告)日：2006-06-29
申请号：US11023856
申请日：2004-12-24
申请人： Harr Chen , Adwait Ratnaparkhi , Sonja Knoll , Hsiao-Wuen Hon
发明人： Harr Chen , Adwait Ratnaparkhi , Sonja Knoll , Hsiao-Wuen Hon
IPC分类号： G06F17/30 , G06F12/00
CPC分类号： G06F17/30663 , G06F17/30705 , G06F17/30867 , Y10S707/99942 , Y10S707/99943
摘要： A computer implemented information retrieval system is provided. The system includes a user input configured to receive a user query relative to the corpus. A machine learning classifier is trained with a first set of training data comprising anchor text relative to at least some of the documents in the corpus. A processing unit is adapted to interact with the classifier to obtain search results relative to the query using the machine learning classifier. In some aspects, the classifier is also trained with a second set of training data. A method of integrating a new document into a corpus of documents is also provided. A method of training a machine learning classifier for retrieving documents from a corpus using two distinct types of training data is also provided.

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式