会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 7. 发明申请
    • RANKING SEARCH RESULTS USING WEIGHTED TOPOLOGIES
    • 使用加权拓扑来排列搜索结果
    • US20130159291A1
    • 2013-06-20
    • US13325081
    • 2011-12-14
    • Samuel IeongNina MishraOr Sheffet
    • Samuel IeongNina MishraOr Sheffet
    • G06F17/30
    • G06Q30/02G06F16/951
    • Identifiers of items generated in response to a query are each ranked in a way that considers the other identified items. Topologies are generated that correspond to features of the identified items. Each topology may be a Markov chain that includes a node for each identified item and directed edges between the nodes. Each directed edge between a node pair has an associated transition probability that represents the likelihood that a hypothetical user would change their preference from a first node in the pair to the second node in the pair when considering the feature associated with the topology. The topologies are weighted according to the relative importance of the features that correspond to the topologies. The weighted topologies are used to generate a stationary distribution of the identified items, and the identified items are ranked using the stationary distribution.
    • 响应于查询生成的项目的标识符都以考虑其他已识别项目的方式进行排名。 生成与所识别项目的特征对应的拓扑。 每个拓扑可以是马尔可夫链,其包括用于每个识别的项目的节点和节点之间的有向边。 节点对之间的每个有向边具有相关联的转移概率,其表示当考虑与拓扑相关联的特征时,假设用户将其优选从该对中的第一节点改变成对中的第二节点的可能性。 根据与拓扑对应的特征的相对重要性,对拓扑进行加权。 加权拓扑用于产生所识别的项目的固定分布,并且使用固定分布对所识别的项目进行排名。
    • 9. 发明申请
    • GENERATING DOMAIN-BASED TRAINING DATA FOR TAIL QUERIES
    • 生成尾部查询的基于域的训练数据
    • US20120271806A1
    • 2012-10-25
    • US13091145
    • 2011-04-21
    • Samuel IeongNina MishraEldar SadikovLi Zhang
    • Samuel IeongNina MishraEldar SadikovLi Zhang
    • G06F17/30
    • G06F16/9535
    • Training data is provided for tail queries based on a phenomena in search engine user behavior—referred to herein as “domain trust”—as an indication of user preferences for individual URLs in search results returned by a search engine for tail queries. Also disclosed are methods for generating training data in a search engine by forming a collection of query+URL pairs, identifying domains in the collection, and labeling each domain. Other implementations are directed ranking search results generated by a search engine by measuring domain trust for each domain corresponding to each URL from among a plurality of URLs and then ranking each URL by its measured domain trust.
    • 根据搜索引擎用户行为(本文称为域信任)的现象,提供了针对尾部查询的训练数据,作为搜索引擎返回的用于尾部查询的搜索结果中的各个URL的用户偏好的指示。 还公开了用于通过形成查询+ URL对的集合,识别集合中的域并且标记每个域来在搜索引擎中生成训练数据的方法。 针对搜索引擎生成的搜索结果,通过测量来自多个URL中的每个URL的每个域的域信任,然后通过其测量的域信任对每个URL进行排序来定向其他实现。
    • 10. 发明申请
    • AUCTION FORMAT SELECTION USING HISTORICAL DATA
    • 使用历史数据拍卖格式选择
    • US20110184802A1
    • 2011-07-28
    • US12692659
    • 2010-01-25
    • Samuel IeongJinsong Tan
    • Samuel IeongJinsong Tan
    • G06Q30/00G06Q10/00G06N5/02
    • G06Q30/08G06Q30/0246G06Q30/0247G06Q30/0275
    • An auction format may be selected pursuant to analyzing and identifying certain statistical patterns in historical data. For example, the choice of auction format may be based on whether bids and quality exhibit correlation, which can be identified in the historical data. By identifying the statistical patterns in the data, one can choose an auction format that can achieve generation of higher revenue. Such techniques allow an auctioneer, such as a search engine, to generate higher revenue than using a fixed auction format. For example, in the context of sponsored search auction, if the value of a click and the probability of a click are positively correlated, the auctioneer generates higher revenue by ranking the advertisers by bids rather than by bids multiplied by quality.
    • 可以根据历史数据中的某些统计模式的分析和识别来选择拍卖格式。 例如,拍卖格式的选择可以基于出价和质量是否表现出相关性,这可以在历史数据中被识别。 通过识别数据中的统计模式,可以选择可以实现更高收入的拍卖格式。 这样的技术允许诸如搜索引擎的拍卖者产生比使用固定拍卖格式更高的收入。 例如,在赞助搜索拍卖的上下文中,如果点击的价值和点击的概率是正相关的,则拍卖者通过以出价而不是出价乘以质量来排列广告商而产生更高的收入。