Web projections: learning from contextual subgraphs of the web
Web projections: learning from contextual subgraphs of the web
复制标题
网络预测：从网络的上下文子图中学习
DOI：
10.1145/1242572.1242636
复制
发表时间：
2007
期刊：
影响因子：
--
通讯作者：
E. Horvitz
中科院分区：
文献类型：
--
作者：
J. Leskovec;S. Dumais;E. Horvitz
网页之间的图形关系已被用于对搜索结果进行排序的方法中。到目前为止，在这些分析中已经使用了特定的图形属性。我们介绍了一种Web投影方法，该方法通过几种方式概括了Web图形关系的先前工作。通过这种方法，我们通过将页面和域的集合投影到更长的Web图上来创建子图，然后使用机器学习来构建将图形属性作为证据的预测模型。我们描述了这种方法，并给出了实验，说明了搜索结果质量预测模型的构建和用户查询重述。
Graphical relationships among Web pages have been exploited inmethods for ranking search results. To date, specific graphicalproperties have been used in these analyses. We introduce a WebProjection methodology that generalizes prior efforts of graphicalrelationships of the web in several ways. With the approach, wecreate subgraphs by projecting sets of pages and domains onto thelarger web graph, and then use machine learning to constructpredictive models that consider graphical properties as evidence. Wedescribe the method and then present experiments that illustrate theconstruction of predictive models of search result quality and userquery reformulation.