IR系统的偏序集表示和相似性比较
Poset representation and similarity comparisons os systems in IR
摘要：
在本文中，我们使用偏序集表示来描述复杂的答案后，IR系统的聚类和排名过程。所考虑的答案可以通过地图表示或文件的专题分项清单提供。偏序集表示，与图论和关系表示开辟了许多新的相似性度量的定义，能够考虑到聚类和排名过程的观点。我们提出了一个一般的方法来构造新的相似性措施，并给出了几个例子。这些措施可以用于半有序分区;此外，在两组答案的比较中，相应的相似性指标是常见答案的呈现等级的递增函数。
英文摘要：
In this paper we are using the poset representation to describe the complex answers given by IR systems after a clustering and ranking processes. The answers considered may be given by cartographical representations or by thematic sub-lists of documents. The poset representation, with the graph theory and the relational representation opens many perspectives in the definition of new similarity measures capable of taking into account both the clustering and ranking processes. We present a general method for constructing new similarity measures and give several examples. These measures can be used for semi-ordered partitions; moreover, in the comparison of two sets of answers, the corresponding similarity indicator is an increasing function of the ranks of presentation of common answers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
