Automatic Classification of Text Databases Through Query Probing
Automatic Classification of Text Databases Through Query Probing
复制标题
通过查询探测对文本数据库进行自动分类
DOI：
10.1007/3-540-45271-0_16
复制
发表时间：
2000
期刊：
影响因子：
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通讯作者：
M. Sahami
中科院分区：
文献类型：
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作者：
Panagiotis G. Ipeirotis;L. Gravano;M. Sahami
网络上的许多文本数据库都“隐藏”在搜索界面后面，它们的文档只能通过查询来访问。传统搜索引擎通常会忽略此类仅搜索数据库的内容。最近，类似雅虎的目录已经开始手动将这些数据库组织成类别，用户可以浏览以查找这些有价值的资源。我们提出了一种新颖的策略来自动对仅搜索文本数据库进行分类。我们的技术首先训练基于规则的文档分类器，然后使用分类器的规则生成探测查询。查询被发送到文本数据库，然后根据它们为每个查询生成的匹配数进行分类。我们报告了一些初步的探索性实验，这些实验表明我们的方法有望自动表征网络上可访问的文本数据库的内容。
Many text databases on the web are “hidden” behind search interfaces, and their documents are only accessible through querying. Traditional search engines typically ignore the contents of such searchonly databases. Recently, Yahoo-like directories have started to manually organize these databases into categories that users can browse to find these valuable resources. We propose a novel strategy to automate the classification of search-only text databases. Our technique starts by training a rule-based document classifier, and then uses the classifier’s rules to generate probing queries. The queries are sent to the text databases, which are then classified based on the number of matches that they produce for each query. We report some initial exploratory experiments that show that our approach is promising to automatically characterize the contents of text databases accessible on the web.