公开(公告)号：US08600968B2

公开(公告)日：2013-12-03

申请号：US13089996

申请日：2011-04-19

申请人： Roman Holenstein ,  Qing Chang ,  Zhenghao Wang ,  Ravi Shahani

发明人： Roman Holenstein ,  Qing Chang ,  Zhenghao Wang ,  Ravi Shahani

IPC分类号： G06F17/30 ,  G06F7/00

CPC分类号： G06F17/30876

摘要： Computer-readable media, computer systems, and computing methods are provided for recommending websites that are relevant to a current website to which a user has navigated. A search engine is used to track a set of websites the user has visited immediately prior to the current website, while predictive model(s) are used to generate a sequence of websites that include the current website and the tracked websites. The sequence is compared against strings of websites within a browser-history log to identify matching strings, where the matching strings include the sequence and a respective candidate website. A probability of relevance is computed from a frequency that each of the matching strings has been visited within a predefined time frame. The probability of relevance for each of the matching strings is ranked against one another to distill the highest-ranked matching strings, which are parsed to extract and present the candidate websites included therein.

摘要翻译： 提供计算机可读介质，计算机系统和计算方法来推荐与用户已经浏览的当前网站相关的网站。 搜索引擎用于跟踪用户在当前网站之前立即访问的一组网站，而使用预测模型来生成包括当前网站和跟踪网站的网站序列。 该序列与浏览器历史日志中的网站字符串进行比较，以识别匹配的字符串，其中匹配的字符串包括序列和相应的候选网站。 从在预定时间帧内已经访问了每个匹配串的频率计算相关概率。 每个匹配字符串的相关概率相互排序，以便蒸馏最高排名的匹配字符串，其被解析以提取和呈现其中包括的候选网站。

公开(公告)号：US20120271805A1

公开(公告)日：2012-10-25

申请号：US13089996

申请日：2011-04-19

申请人： Roman Holenstein ,  Qing (Elaine) Chang ,  Zhenghao Wang ,  Ravi Shahani

发明人： Roman Holenstein ,  Qing (Elaine) Chang ,  Zhenghao Wang ,  Ravi Shahani

IPC分类号： G06F17/30

CPC分类号： G06F17/30876

摘要： Computer-readable media, computer systems, and computing methods are provided for recommending websites that are relevant to a current website to which a user has navigated. A search engine is used to track a set of websites the user has visited immediately prior to the current website, while predictive model(s) are used to generate a sequence of websites that include the current website and the tracked websites. The sequence is compared against strings of websites within a browser-history log to identify matching strings, where the matching strings include the sequence and a respective candidate website. A probability of relevance is computed from a frequency that each of the matching strings has been visited within a predefined time frame. The probability of relevance for each of the matching strings is ranked against one another to distill the highest-ranked matching strings, which are parsed to extract and present the candidate websites included therein.

摘要翻译： 提供计算机可读介质，计算机系统和计算方法来推荐与用户已经浏览的当前网站相关的网站。 搜索引擎用于跟踪用户在当前网站之前立即访问的一组网站，而使用预测模型来生成包括当前网站和被跟踪网站的一系列网站。 该序列与浏览器历史日志中的网站字符串进行比较，以识别匹配的字符串，其中匹配的字符串包括序列和相应的候选网站。 从在预定时间帧内已经访问了每个匹配串的频率计算相关概率。 每个匹配字符串的相关概率相互排序，以便蒸馏最高排名的匹配字符串，其被解析以提取和呈现其中包括的候选网站。