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首页> 外文期刊>International Journal of Production Research >Mining relevant information on the Web: a clique-based approach
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Mining relevant information on the Web: a clique-based approach

机译：在网络上挖掘相关信息：一种基于团体的方法

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摘要

The role of information management and retrieval in production processes has been gaining in importance in recent years. In this context, the ability to search for and quickly find the small piece of information needed from the huge amount of information available has crucial importance. One category of tools devoted to such a task is represented by search engines. Satisfying the basic needs of the Web user has led to the research of new tools that aim at helping more sophisticated users (communities, companies, interest groups) with more elaborate methods. An example is the use of clustering and classification algorithms or other specific data mining techniques. In such a context, the proper use of a thematic search engine is a crucial tool in supporting and orienting many activities. Several practical and theoretical problems arise in developing such tools, and we try to face some of these in this paper, extending previous work on Web mining. Here we consider two related problems: how to select an appropriate set of keywords for a thematic engine taking into account the semantic and linguistic extensions of the search context, and how to select and rank a subset of relevant pages given a set of search keywords. Both problems are solved using the same framework, based on a graph representation of the available information and on the search of particular node subsets of such a graph. Such subsets are effectively identified by a maximum-weight clique algorithm customized ad hoc for specific problems. The methods have been developed in the framework of a funded research project for the development of new Web search tools, they have been tested on real data, and are currently being implemented in a prototypal thematic search engine. The Web mining method presented in this paper can be applied to Web-based design and manufacturing.
机译：近年来，信息管理和检索在生产过程中的作用越来越重要。在这种情况下，从大量可用信息中搜索并快速找到所需的一小部分信息的能力至关重要。搜索引擎代表了用于执行此类任务的一类工具。满足Web用户的基本需求导致了对新工具的研究，这些新工具旨在通过更精细的方法来帮助更复杂的用户（社区，公司，利益集团）。一个例子是使用聚类和分类算法或其他特定的数据挖掘技术。在这种情况下，正确使用主题搜索引擎是支持和指导许多活动的关键工具。开发此类工具时会遇到一些实际和理论上的问题，我们将在本文中尝试解决其中的一些问题，以扩展先前有关Web挖掘的工作。在这里，我们考虑两个相关的问题：如何为主题引擎选择适当的一组关键字，同时考虑到搜索上下文的语义和语言扩展，以及如何在给定一组搜索关键字的情况下选择相关页面的子集并对其进行排名。基于可用信息的图形表示以及这种图形的特定节点子集的搜索，使用相同的框架解决了这两个问题。通过针对特定问题定制的最大权重派系算法可以有效地识别此类子集。这些方法是在一个资助研究项目的框架内开发的，用于开发新的Web搜索工具，已经在真实数据上进行了测试，目前正在原型主题搜索引擎中实施。本文提出的Web挖掘方法可以应用于基于Web的设计和制造。

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