How the dragons work: searching in a web

I. Witten
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引用次数: 1

Abstract

Search engines -- "web dragons" -- are the portals through which we access society's treasure trove of information. They do not publish the algorithms they use to sort and filter information, yet how they work is one of the most important questions of our time. Google's PageRank is a way of measuring the prestige of each web page in terms of who links to it: it reflects the experience of a surfer condemned to click randomly around the web forever. The HITS technique distinguishes "hubs" that point to reputable sources from "authorities," the sources themselves. This helps differentiate communities on the web, which in turn can tease out alternative interpretations of ambiguous query terms. RankNet uses machine learning techniques to rank documents by predicting relevance judgments based on training data. This article explains in non-technical terms how the dragons work.
龙是如何工作的:在网上搜索
搜索引擎——“网络巨龙”——是我们获取社会信息宝库的门户。他们没有公布他们用来分类和过滤信息的算法,但它们是如何工作的是我们这个时代最重要的问题之一。b谷歌的PageRank是一种衡量每个网页的声望的方法,根据链接到它的人来衡量:它反映了一个被谴责永远在网络上随机点击的冲浪者的体验。HITS技术将指向信誉良好的资源的“中心”与资源本身的“权威”区分开来。这有助于区分网络上的社区,这反过来又可以梳理出模棱两可的查询术语的替代解释。RankNet使用机器学习技术通过预测基于训练数据的相关性判断来对文档进行排名。本文用非技术术语解释龙是如何工作的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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