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    • 2. 发明申请
    • Algorithm for tree traversals using left links
    • 使用左链接的树遍历算法
    • US20060026188A1
    • 2006-02-02
    • US11219140
    • 2005-09-01
    • Marc NajorkChandramohan Thekkath
    • Marc NajorkChandramohan Thekkath
    • G06F7/00
    • G06F17/30958Y10S707/918Y10S707/99944
    • An information management system includes a computer and a database comprising a B-Tree data structure comprising a plurality of nodes associated with disk blocks and handles stored in the nodes. At least one left-link handle, hleft, stored in each node points to a left sibling of that node. A mechanism for performing a lookup operation with respect to a key, k, traverses the B-Tree and refers to the left-link handle, hleft, of a node to access a left sibling of the node if the key k is less than or equal to a value kmin stored in the node. Mechanisms are also provided for performing insert and delete operations, and the lookup, insert, and delete operations detect if the key range of an index node, A, does not include the key k that the operation is trying to locate, and follow a handle A.hleft to the left sibling when k≦A.kmin.
    • 信息管理系统包括计算机和包括B-Tree数据结构的数据库,该B-Tree数据结构包括与磁盘块相关联的多个节点和存储在节点中的句柄。 存储在每个节点中的至少一个左链接句柄h 指向该节点的左兄弟节点。 用于执行关于密钥k的查找操作的机制遍历B树并且参考节点的左链接句柄html左侧来访问节点的左兄弟节点 如果密钥k小于或等于存储在节点中的值k分钟。 还提供了用于执行插入和删除操作的机制,并且查找,插入和删除操作检测索引节点A的关键范围是否不包括操作正在查找的密钥k,并遵循句柄 当k <= AK分钟时,向左兄弟姐妹左边
    • 5. 发明申请
    • Systems and methods for ranking documents based upon structurally interrelated information
    • 基于结构相关信息对文档进行排序的系统和方法
    • US20050060297A1
    • 2005-03-17
    • US10663933
    • 2003-09-16
    • Marc Najork
    • Marc Najork
    • G06F17/00G06F12/00G06F13/00G06F17/20G06F17/30G06F7/00
    • G06F17/30864
    • Systems and methods for ranking Web pages based on hyperlink information in a manner that is resistant to nepotistic links are provided. In one embodiment, a Web search service is provided for returning quality query results. The vulnerability of existing ranking algorithms, such as PageRank, to Web pages that are artificially generated for the sole purpose of inflating the score of target page(s) is addressed. Intuitively, it is recognized that it is less likely to reach a particular page on a Web server having many pages via a random jump than it is to reach a particular page on a Web server having few pages, which implies that the influence of such a page upon another page by linking to, or endorsing, the other page is diminished. Thus, in various non-limiting embodiments, each Web server, not each Web page, is assigned a guaranteed minimum score. This minimum score assigned to a server can then be divided among all the pages on that Web server.
    • 提供了一种基于超链接信息对网页进行排序的系统和方法,该方法具有耐人关联的方式。 在一个实施例中,提供了用于返回质量查询结果的Web搜索服务。 现有的排名算法(例如PageRank)对仅为了提高目标页面得分而人为地产生的网页的漏洞被解决。 直观地认识到,不太可能通过随机跳转到达具有许多页面的Web服务器上的特定页面,而不是到达具有几页的Web服务器上的特定页面,这意味着这样的 通过链接到另一个页面或批注另一个页面的页面被减少。 因此,在各种非限制性实施例中,每个Web服务器(而不是每个网页)被分配有保证的最小分数。 分配给服务器的最小分数可以在该Web服务器上的所有页面之间分配。
    • 6. 发明申请
    • SOCIAL NETWORK RECOMMENDED CONTENT AND RECOMMENDING MEMBERS FOR PERSONALIZED SEARCH RESULTS
    • 社会网络推荐内容和推荐会员个人搜索结果
    • US20130086057A1
    • 2013-04-04
    • US13252215
    • 2011-10-04
    • Timothy HarringtonRajesh ShenoyMarc NajorkRina Panigrahy
    • Timothy HarringtonRajesh ShenoyMarc NajorkRina Panigrahy
    • G06F17/30
    • H04L51/32G06F17/30864
    • Architecture that provides a data structure to facilitate personalized ranking over recommended content (e.g., documents). The data structure approximates the social distance of the searching user to the content at query time. A graph is created of content recommended by members of the social network, where the nodes of the graph include content nodes (for the content) and recommending member nodes (for members of the social network who recommended the content). If a member recommends content, an edge is created between the member node and the content node. If a member is a “friend” (tagged as related in some way) of another member, an edge is created between the two member nodes. Each node is converted to a lower dimensional feature set. Feature sets of the content are indexed and the feature set of the searching user is utilized to match and rank the search results at query time.
    • 提供数据结构以促进针对推荐内容(例如,文档)的个性化排名的架构。 数据结构近似于搜索用户在查询时的内容的社交距离。 创建由社交网络成员推荐的内容的图形,其中图的节点包括内容节点(用于内容)和推荐成员节点(为推荐内容的社交网络的成员)。 如果成员建议内容,则会在成员节点和内容节点之间创建边。 如果一个成员是另一个成员的朋友(以某种方式标记为相关),则在两个成员节点之间创建一个边。 每个节点都转换为较低维度的特征集。 内容的特征集被索引,并且利用搜索用户的特征集来在查询时间匹配和排列搜索结果。
    • 7. 发明申请
    • Systems and methods for inferring uniform resource locator (URL) normalization rules
    • 用于推导统一资源定位符(URL)规范化规则的系统和方法
    • US20060218143A1
    • 2006-09-28
    • US11089988
    • 2005-03-25
    • Marc Najork
    • Marc Najork
    • G06F17/30
    • G06F17/30864Y10S707/99935
    • Different URLs that actually reference the same web page or other web resource are detected and that information is used to only download one instance of a web page or web resource from a web site. All web pages or web resources downloaded from a web server are compared to identify which are substantially identical. Once identical web pages or web resources with different URLs are found, the different URLs are then analyzed to identify what portions of the URL are essential for identifying a particular web page or web resource, and what portions are irrelevant. Once this has been done for each set of substantially identical web pages or web resources (also referred to as an “equivalence class” herein), these per-equivalence-class rules are generalized to trans-equivalence-class rules. There are two rule-learning steps: step (1), where it is learned for each equivalence class what portions of the URLs in that class are relevant for selecting the page and what portions are not; and step (2), where the per-equivalence-class rules constructed during step (1) are generalized to rules that cover many equivalence classes. Once a rule is determined, it is applied to the class of web pages or web resources to identify errors. If there are no errors, the rule is activated and is then used by the web crawler for future crawling to avoid the download of duplicative web pages or web resources.
    • 检测到实际引用相同网页或其他网络资源的不同URL,并且该信息用于仅从网站下载一个网页或网页资源的一个实例。 将从Web服务器下载的所有网页或网络资源进行比较,以确定哪些基本相同。 一旦找到具有不同URL的相同的网页或网页资源,就分析不同的URL来识别URL的哪些部分对于识别特定的网页或web资源是必不可少的,哪些部分是不相关的。 一旦对每组基本相同的网页或网络资源(在本文中也称为“等价类”)进行了这一操作,这些每等价类规则被推广到跨等价类规则。 有两个规则学习步骤:步骤(1),其中为每个等价类学习,该类中的URL的哪些部分与选择页面和哪些部分不相关? 和步骤(2),其中在步骤(1)中构造的每等价类规则被推广到覆盖许多等价类的规则。 一旦确定规则,它将被应用于网页或网页资源类别以识别错误。 如果没有错误,该规则将被激活,然后被网络爬网程序用于将来的抓取,以避免下载重复的网页或Web资源。
    • 8. 发明授权
    • Social network recommended content and recommending members for personalized search results
    • 社交网络推荐内容,推荐会员查询个性化搜索结果
    • US08949232B2
    • 2015-02-03
    • US13252215
    • 2011-10-04
    • Timothy HarringtonRajesh ShenoyMarc NajorkRina Panigrahy
    • Timothy HarringtonRajesh ShenoyMarc NajorkRina Panigrahy
    • G06F17/30H04L12/58
    • H04L51/32G06F17/30864
    • Architecture that provides a data structure to facilitate personalized ranking over recommended content (e.g., documents). The data structure approximates the social distance of the searching user to the content at query time. A graph is created of content recommended by members of the social network, where the nodes of the graph include content nodes (for the content) and recommending member nodes (for members of the social network who recommended the content). If a member recommends content, an edge is created between the member node and the content node. If a member is a “friend” (tagged as related in some way) of another member, an edge is created between the two member nodes. Each node is converted to a lower dimensional feature set. Feature sets of the content are indexed and the feature set of the searching user is utilized to match and rank the search results at query time.
    • 提供数据结构以促进针对推荐内容(例如,文档)的个性化排名的架构。 数据结构近似于搜索用户在查询时的内容的社交距离。 创建由社交网络成员推荐的内容的图形,其中图的节点包括内容节点(用于内容)和推荐成员节点(为推荐内容的社交网络的成员)。 如果成员建议内容,则会在成员节点和内容节点之间创建一个边。 如果一个成员是另一个成员的“朋友”(以某种方式标记为相关),则在两个成员节点之间创建一个边。 每个节点都转换为较低维度的特征集。 内容的特征集被索引,并且利用搜索用户的特征集来在查询时间匹配和排列搜索结果。
    • 9. 发明申请
    • Domain-based spam-resistant ranking
    • 基于域的垃圾邮件排名
    • US20070067282A1
    • 2007-03-22
    • US11230784
    • 2005-09-20
    • Amit PrakashMichael NarayanDarren ShakibMarc Najork
    • Amit PrakashMichael NarayanDarren ShakibMarc Najork
    • G06F17/30
    • G06F16/951
    • A domain-based spam-resistant ranking architecture that computes trust in a domain based on web-servers on which a domain is hosted and a set of other domains that link to the domain. The ranks of pages are computed based on how much trust there is in each domain and which pages link to it. Web documents are ranked in a spam-resistant manner by assigning uniform significance to each IP address of a network location and then assigning trust values to domains hosted on those IP addresses. Then, based on a domain graph, the invention constructs a domain-rank which is an estimate of how authoritative the domain is. The domain ranks are then used to assign a minimum rank to each document.
    • 基于域的基于垃圾邮件的排名体系结构,可以根据托管域的Web服务器和一组链接到该域的其他域来计算域中的信任。 页面的排名是根据每个域中的信任度以及链接到哪个页面来计算的。 通过为网络位置的每个IP地址分配均匀的重要性,然后为托管在这些IP地址上的域分配信任值,将Web文档排列为垃圾邮件的方式。 然后,基于域图,本发明构造了一个域级,其是该域的权威性的估计。 然后,域排名用于为每个文档分配最低等级。
    • 10. 发明申请
    • Incremental update scheme for hyperlink database
    • 超链接数据库的增量更新方案
    • US20070250480A1
    • 2007-10-25
    • US11408283
    • 2006-04-19
    • Marc Najork
    • Marc Najork
    • G06F17/30
    • G06F17/30864
    • A database of hyperlinks, stored in a hyperlink store or distributed across multiple machines such as a scalable hyperlink store, may be incrementally updated. When data is added, instead of modifying an existing data store, a hierarchy of data stores is built. The data stores are merged together, such that a new store is a suffix on an old store. Additions and updates go into new stores, which are relatively small. Lookups consult new stores first. A background thread merges adjacent stores. For example, a batch of updates is collected and incorporated into a new store and then the store is sealed. Subsequent updates are added to yet another new store. Stores are merged occasionally to prevent the chain of stores from becoming too long. Once the batch has been integrated, the new stores are sealed and are used to answer subsequent queries.
    • 可以递增地更新存储在超链接中存储或分布在多个机器(例如可伸缩超链接存储)上的超链接的数据库。 当添加数据时,不是修改现有的数据存储,而是构建数据存储层次结构。 数据存储被合并在一起,使得新商店是旧商店的后缀。 添加和更新进入新的商店,这些商店相对较小。 Lookups首先咨询新店。 背景线程合并相邻商店。 例如,收集一批更新并将其合并到新的商店中,然后密封商店。 随后的更新添加到另一个新商店。 商店偶尔合并,以防止商店连锁店变得太长。 一旦批量被集成,新的商店被密封并用于回答随后的查询。