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    • 3. 发明申请
    • Block tracking mechanism for web personalization
    • 网站个性化的块跟踪机制
    • US20080281834A1
    • 2008-11-13
    • US11801404
    • 2007-05-09
    • Min WuChenxi LinBenyu ZhangHuajun ZengZheng ChenJian Wang
    • Min WuChenxi LinBenyu ZhangHuajun ZengZheng ChenJian Wang
    • G06F17/30
    • G06F17/30861
    • Described is a technology by which blocks of web pages may be selected, such as for building a user-personalized web page containing selected blocks. A selection mechanism, such as a browser toolbar add-on, provides a user interface for selecting blocks, and records information about selected blocks. A block tracking mechanism (e.g., a daemon program) uses the information to locate selected blocks of the web pages, including when the web page containing the block is updated with respect to content and/or layout. The block tracking mechanism may update a local gadget that when invoked, such as by browsing to a particular web page, which shows updated versions of the block on a personalized web page. Blocks may be efficiently located by processing trees representing web pages into reduced trees, and then by performing a minimum distance mapping algorithm on the reduced trees.
    • 描述了可以选择网页块的技术,诸如用于构建包含所选块的用户个性化网页。 诸如浏览器工具栏附件的选择机制提供用于选择块的用户界面,并且记录关于所选块的信息。 块跟踪机制(例如,守护程序)使用该信息来定位网页的所选块,包括当包含块的网页相对于内容和/或布局被更新时。 块跟踪机制可以更新当调用时​​的本地小工具,诸如通过浏览到特定网页,其显示个性化网页上块的更新版本。 可以通过将表示网页的树处理成缩小的树,然后通过在缩小的树上执行最小距离映射算法来有效地定位块。
    • 5. 发明授权
    • Efficient retrieval algorithm by query term discrimination
    • 通过查询词辨别的有效检索算法
    • US07822752B2
    • 2010-10-26
    • US11804627
    • 2007-05-18
    • Chenxi LinLei JiHuajun ZengBenyu ZhangZheng ChenJian Wang
    • Chenxi LinLei JiHuajun ZengBenyu ZhangZheng ChenJian Wang
    • G06F7/00G06F17/30
    • G06F17/30675
    • Described is an efficient retrieval mechanism that quickly locates documents (e.g., corresponding to online advertisements) based on query term discrimination. A topmost subset (e.g., two) of search terms is selected according to their ranked importance, e.g., as ranked by inverted document frequency. The topmost terms are then used to narrow the number of rows of an inverted query index that are searched to find document identifiers and associated scores, such as computed offline by a BM25 algorithm. For example, for each document identifier of each important term, a fast search within each of the narrowed subset of rows (that also contain that document identifier) may be performed by comparing document identifiers to jump a pointer within each other row, followed by a binary search to locate a particular document. The scores of the set of particular documents may then be used to rank their relative importance for returning as results.
    • 描述了一种有效的检索机制,其基于查询词辨别快速定位文档(例如,对应于在线广告)。 根据其排序的重要性来选择搜索项的最顶层子集(例如,两个),例如按照倒排的文档频率排序。 然后使用最上面的术语来缩小被搜索以查找文档标识符和相关分数的反向查询索引的行数,例如通过BM25算法离线计算。 例如,对于每个重要术语的每个文档标识符,可以通过比较文档标识符来跳过每个其他行中的指针,然后是一个指针,来执行每个狭窄的行子集(也包含该文档标识符)的快速搜索 二进制搜索查找特定文档。 然后可以使用该组特定文件的分数来排列其作为结果返回的相对重要性。
    • 7. 发明申请
    • Efficient Retrieval Algorithm by Query Term Discrimination
    • 通过查询词辨别的有效检索算法
    • US20080215574A1
    • 2008-09-04
    • US12038652
    • 2008-02-27
    • Chenxi LinLei JiHuaJun ZengBenyu ZhangZheng ChenJian Wang
    • Chenxi LinLei JiHuaJun ZengBenyu ZhangZheng ChenJian Wang
    • G06F17/30
    • G06F17/30675G06Q10/10
    • An exemplary method for use in information retrieval includes, for each of a plurality of terms, selecting a predetermined number of top scoring documents for the term to form a corresponding document set for the term; receiving a plurality of terms, optionally as a query; ranking the plurality of terms for importance based at least in part on the document sets for the plurality of terms where the ranking comprises using an inverse document frequency algorithm; selecting a number of ranked terms based on importance where each selected, ranked term comprises its corresponding document set wherein each document in a respective document set comprises a document identification number; forming a union set based on the document sets associated with the selected number of ranked terms; and, for a document identification number in the union set, scanning a document set corresponding to an unselected term for a matching document identification number. Various other exemplary systems, methods, devices, etc. are also disclosed.
    • 用于信息检索的示例性方法包括对于多个术语中的每一个,为该术语选择预定数量的最高评分文档以形成用于该术语的对应文档集合; 接收多个术语,可选地作为查询; 至少部分地基于所述多个术语的文档集来排序所述多个重要项,所述术语的排序包括使用逆文档频率算法; 基于重要性选择多个排名项,其中每个所选择的排名项包括其对应的文档集,其中相应文档集中的每个文档包括文档标识号; 基于与选定数量的排名项相关联的文档集合来形成联合集合; 并且对于联合集合中的文档识别号码,扫描与匹配文档识别号码的未选择的术语相对应的文档集。 还公开了各种其它示例性系统,方法,装置等。
    • 8. 发明授权
    • Block tracking mechanism for web personalization
    • 网站个性化的块跟踪机制
    • US07818330B2
    • 2010-10-19
    • US11801404
    • 2007-05-09
    • Min WuChenxi LinBenyu ZhangHuajun ZengZheng ChenJian Wang
    • Min WuChenxi LinBenyu ZhangHuajun ZengZheng ChenJian Wang
    • G06F7/00
    • G06F17/30861
    • Described is a technology by which blocks of web pages may be selected, such as for building a user-personalized web page containing selected blocks. A selection mechanism, such as a browser toolbar add-on, provides a user interface for selecting blocks, and records information about selected blocks. A block tracking mechanism (e.g., a daemon program) uses the information to locate selected blocks of the web pages, including when the web page containing the block is updated with respect to content and/or layout. The block tracking mechanism may update a local gadget that when invoked, such as by browsing to a particular web page, which shows updated versions of the block on a personalized web page. Blocks may be efficiently located by processing trees representing web pages into reduced trees, and then by performing a minimum distance mapping algorithm on the reduced trees.
    • 描述了可以选择网页块的技术,诸如用于构建包含所选块的用户个性化网页。 诸如浏览器工具栏附件的选择机制提供用于选择块的用户界面,并且记录关于所选块的信息。 块跟踪机制(例如,守护程序)使用该信息来定位网页的所选块,包括当包含块的网页相对于内容和/或布局被更新时。 块跟踪机制可以更新当调用时​​的本地小工具,诸如通过浏览到特定网页,其显示个性化网页上块的更新版本。 可以通过将表示网页的树处理成缩小的树,然后通过在缩小的树上执行最小距离映射算法来有效地定位块。
    • 9. 发明申请
    • Ranking online advertisements using retailer and product reputations
    • 使用零售商和产品信誉排名在线广告
    • US20080288348A1
    • 2008-11-20
    • US11803461
    • 2007-05-15
    • Huajun ZengChenxi LinDingyi HanBenyu ZhangZheng ChenJian Wang
    • Huajun ZengChenxi LinDingyi HanBenyu ZhangZheng ChenJian Wang
    • G06Q30/00
    • G06Q30/02G06Q30/0254G06Q30/0256G06Q30/0263G06Q30/0277
    • A method for ranking online advertisements using retailer reputation and product reputation. In one implementation, a query may be received. Advertisements may be selected by determining a level of relevance between the query and each advertisement and selecting the advertisements with a level of relevance above a pre-determined level of relevance. A predicted reputation for a retailer and a predicted reputation for a product may be retrieved for each of the selected advertisements. The selected advertisements may then be ranked based on the predicted reputation for the retailer and the predicted reputation of the product. The ranking of the selected advertisements may be accomplished by calculating a ranking score for each selected advertisement based on the retailer predicted reputation and the product predicted reputation. The selected advertisements may then be displayed according to the ranking.
    • 使用零售商信誉和产品信誉对在线广告进行排名的方法。 在一个实现中,可以接收查询。 可以通过确定查询和每个广告之间的相关性级别并且选择具有相关性水平高于预定相关性水平的广告来选择广告。 可以为每个选定的广告检索零售商的预测声誉和产品的预测声誉。 所选择的广告然后可以基于零售商的预测信誉和产品的预测声誉进行排名。 所选择的广告的排名可以通过基于零售商预测的声誉和产品预测的声誉来计算每个所选广告的排名得分来实现。 然后可以根据排名显示所选择的广告。
    • 10. 发明申请
    • Efficient retrieval algorithm by query term discrimination
    • 通过查询词辨别的有效检索算法
    • US20080288483A1
    • 2008-11-20
    • US11804627
    • 2007-05-18
    • Chenxi LinLei JiHuajun ZengBenyu ZhangZheng ChenJian Wang
    • Chenxi LinLei JiHuajun ZengBenyu ZhangZheng ChenJian Wang
    • G06F17/30
    • G06F17/30675
    • Described is an efficient retrieval mechanism that quickly locates documents (e.g., corresponding to online advertisements) based on query term discrimination. A topmost subset (e.g., two) of search terms is selected according to their ranked importance, e.g., as ranked by inverted document frequency. The topmost terms are then used to narrow the number of rows of an inverted query index that are searched to find document identifiers and associated scores, such as computed offline by a BM25 algorithm. For example, for each document identifier of each important term, a fast search within each of the narrowed subset of rows (that also contain that document identifier) may be performed by comparing document identifiers to jump a pointer within each other row, followed by a binary search to locate a particular document. The scores of the set of particular documents may then be used to rank their relative importance for returning as results.
    • 描述了一种有效的检索机制,其基于查询词辨别快速定位文档(例如,对应于在线广告)。 根据其排序的重要性来选择搜索项的最顶层子集(例如,两个),例如按照倒排的文档频率排序。 然后使用最上面的术语来缩小被搜索以查找文档标识符和相关分数的反向查询索引的行数,例如通过BM25算法离线计算。 例如,对于每个重要术语的每个文档标识符,可以通过比较文档标识符来跳过每个其他行中的指针,然后是一个指针,来执行每个狭窄的行子集(也包含该文档标识符)的快速搜索 二进制搜索查找特定文档。 然后可以使用该组特定文件的分数来排列其作为结果返回的相对重要性。