使用共引用的元数据在Web中的传播

Camille Prime-Claverie, M. Beigbeder, T. Lafouge
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引用次数: 4

摘要

考虑到万维网的巨大异质性,在搜索引擎端使用元数据似乎是信息检索的有用途径。但是,由于无法获得Web规模的手动鉴定,因此很少有人遵循这条路线。我们提出了一种半自动的元数据传播方法。第一步,提取同构语料库。我们在研究中使用了以下属性:权限类型、站点类型、信息类型和页面类型。第一步是通过基于页面间共引频率的相似性度量的聚类来实现的。给定集群层次结构,第二步选择需要手动限定的较少数量的文档,并将给定的元数据值传播给属于同一集群的其他文档。对该方法的可扩展性进行了定性评价和初步研究。
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Metadata propagation in the Web using co-citations
Given the large heterogeneity of the World Wide Web, using metadata on the search engines side seems to be a useful track for information retrieval. Though, because a manual qualification at the Web scale is not accessible, this track is little followed. We propose a semi-automatic method for propagating metadata. In a first step, homogeneous corpus are extracted. We used in our study the following properties: the authority type, the site type, the information type, and the page type. This first step is realized by a clusterization which uses a similarity measure based on the co-citation frequency between pages. Given the cluster hierarchy, the second step selects a reduced number of documents to be manually qualified and propagates the given metadata values to the other documents belonging to the same cluster. A qualitative evaluation and a preliminary study about the scalability of this method are presented.
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