WIM:用于Web的信息挖掘模型

Ricardo Baeza-Yates, Álvaro R. Pereira, N. Ziviani
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引用次数: 7

摘要

本文提出了一种基于Web和图形分析的信息挖掘模型,即Web信息挖掘模型(WIM)。我们使用Web仓库演示模型特征。仓库中的Web数据建模为图,其中节点表示Web页面,边表示超链接。在模型中,对象总是节点的集合,并且属于一个类。我们有包含直接从Web页面和链接获得的属性的物理对象,如Web页面的标题或链接的开始页和结束页。可以通过对任何现有对象执行预定义的操作来创建逻辑对象。本文给出了模型的组成部分,提出了一组11个操作符,并给出了视图示例。视图是对对象的一系列操作,它代表了在图中挖掘信息的一种方式。作为实际示例,我们提供了用于集群节点和标识相关项集的视图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WIM: an information mining model for the Web
This paper presents a model to mine information in applications involving Web and graph analysis, referred to as WIM - Web information mining - model. We demonstrate the model characteristics using a Web warehouse. The Web data in the warehouse is modeled as a graph, where nodes represent Web pages and edges represent hyperlinks. In the model, objects are always sets of nodes and belong to one class. We have physical objects containing attributes directly obtained from Web pages and links, as the title of a Web page or the start and end pages of a link. Logical objects can be created by performing predefined operations on any existing object. In this paper we present the model components, propose a set of eleven operators and give examples of views. A view is a sequence of operations on objects, and it represents a way to mine information in the graph. As practical examples, we present views for clustering nodes and for identifying related item sets.
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