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A Metaphoric Search Method for HTML documents

HTML文档的隐喻搜索方法

基本信息

批准号：
13480086
负责人：
HARAGUCHI Makoto
金额：
$ 3.33万
依托单位：
Hokkaido University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2001
资助国家：
日本
起止时间：
2001 至 2003
项目状态：
已结题

项目摘要

Normally, it is troublesome task for users of search engines to represent their intention explicitly beforehand. This is one of major reasons why the search results do not meet user's intention in many cases. Instead of presenting queries describing those intentions precisely, we suppose as a query a pair of an abstract query and its examples. What to be searched is an instance of the abstract one similar to the examples. In other words, our search task is to "find an instance of the abstract one like examples". An HTML document, the object of our search task, can be viewed as a rooted tree of tags with some text contents as its leaves. In order to judge the similarities between text contents and tag structure as well, we consider an ordering on the class of concept graph representations. Both instance generalization relationship and similarity relationship can be defined in terms of the ordering. Based on this fundamental structure of objects for our search problem, we have developed an algorithm to find an instance of abstract query, given its examples. That is, it first computes a set of segments of sentences in text contents from the abstract query Secondly, by matching those text segments, it forms an instance of the query that is a generalization of the given example documents. Finally, any document subsumed by the instance is regarded relevant to the initial query Our experimental result shows that it can compute the generalized document of about 50 sentences within 3 seconds.

通常情况下，搜索引擎的用户要事先明确地表达他们的意图是一件很麻烦的事情。这是搜索结果在许多情况下不符合用户意图的主要原因之一。而不是提出查询描述这些意图精确，我们假设作为一个查询一对抽象的查询和它的例子。所要搜索的是与示例相似的抽象的实例。换句话说，我们的搜索任务是“找到一个抽象的例子”。HTML文档（我们搜索任务的对象）可以被视为标记的根树，其中一些文本内容作为其叶子。为了判断文本内容和标签结构之间的相似性，我们考虑了概念图表示类的排序。实例泛化关系和实例相似关系都可以按照顺序来定义。基于这个基本结构的对象为我们的搜索问题，我们已经开发了一个算法来找到一个实例的抽象查询，给出了它的例子。也就是说，它首先从抽象查询中计算文本内容中的句子片段的集合。其次，通过匹配这些文本片段，它形成查询的实例，该实例是给定示例文档的概括。实验结果表明，该算法可以在3秒内计算出约50个句子的广义文档。