将PageRank应用于主题层次结构树（使用从DBpedia提取的SPARQL查询） [英] Applying PageRank to a topic hierarchy tree(using SPARQL query extracted from DBpedia)

问题描述

由于我有一个DBpedia查询，我想使用PageRank算法对这些结果进行排名。

As I have a DBpedia query and I want to rank those results by using the PageRank algorithm.

对于概念 Machine_learning，通过使用下面的SPARQL查询，我可以找出所有DBpedia中的ParentNode，ChildNode和SiblingNodes。

Toward the concept "Machine_learning", by using the SPARQL query below, I can find out all the ParentNodes, ChildNodes and SiblingNodes in DBpedia.

select * where {
{ ?childNodes skos:broader <http://dbpedia.org/resource/Category:Machine_learning> . ?childNodes skos:broader ?siblingConceptsFormChildNodes}
UNION
{<http://dbpedia.org/resource/Category:Machine_learning> skos:broader ?parentNodes . ?siblingConceptsFormParentNodes skos:broader ?parentNodes}
}

对于可视化，主题层次结构将如下所示：
受管制的概念图

For the visualization, the topic hierarchy would be like this: Regulated concept map

您可能会发现主题层次结构是基于SKOS：broader和SKOS：narrower属性的。

As you may found that the topic hierarchy is based on the SKOS:broader and SKOS:narrower properties.

我的意图是通过PageRank对主题层次结构中存在的所有节点进行排名。上面查询的结果是有限的。

My intention is to rank all the nodes exist in the topic hierarchy by PageRank. The results from the query above are limited.

我还发现了一个与我的问题有关的问题：
如何使用DBpedia属性来构建主题层次结构？

And I also found out this question that seems related to my question: How to use DBpedia properties to build a topic hierarchy?

但是，我认为我们之间的方法有些不同。

However, I think the approach between us is a bit different.

我还针对上述主题层次结构调整了PageRank算法：

I also adjust the PageRank algorithm for the topic hierarchy above:

PageRank算法

谢谢

推荐答案

如果尚未解决问题，则可以考虑将DBpedia数据加载到Anzograph中，然后使用内置服务。在此处查看文档和示例 https://docs.cambridgesemantics.com/anzograph /v2.2/userdoc/pagerank.htm

If you have not already solved your problem, you might consider loading the DBpedia data into Anzograph and then using the built-in service. See docs and examples here https://docs.cambridgesemantics.com/anzograph/v2.2/userdoc/pagerank.htm

免责声明：我在Cambridge Semantics Inc.工作。

Disclaimer: I work for Cambridge Semantics Inc.

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