搜索排名/相关算法 [英] Search ranking/relevance algorithms

问题描述

在开发的文章在知识库（例如）的数据库 - 什么是排序并显示最相关的答案，一个用户的问题的最佳途径。

When developing a database of articles in a Knowledge Base (for example) - what are the best ways to sort and display the most relevant answers to a users' question?

你会使用基于是否previous用户发现帮助的文章更多的数据，如关键词的权重，或者你找一个简单的关键字匹配算法是足够的？

Would you use additional data such as keyword weighting based on whether previous users found the article of help, or do you find a simple keyword matching algorithm to be sufficient?

推荐答案

也许这将立即给予最简单，最朴素的方法有用的结果将是实施的 * TF-IDF ：

Perhaps the easiest and most naive approach that will give immediately useful results would be to implement *tf-idf:

在TF-IDF权重方案的变化经常被搜索引擎作为得分的核心工具和排名文档的相关性给用户查询。 TF-IDF可以成功地用于中止词在不同的学科领域包括文字总结和分类过滤。

Variations of the tf–idf weighting scheme are often used by search engines as a central tool in scoring and ranking a document's relevance given a user query. tf–idf can be successfully used for stop-words filtering in various subject fields including text summarization and classification.

在这里的矿井最近的相关问题，我学​​到了一个极好的免费书籍关于这个主题，你可以下载或在线阅读的：

In a recent related question of mine here I learned of an excellent free book on this topic which you can download or read online:

的现代信息检索

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