标题:
基于社交网络的实时搜索引擎探究Study on Real-Time Search Engine Based on Social Network
作者:
黄正伟, 黄会娟, 杨艳妮
关键字:
实时搜索, 传统搜索, 社交网络Real-Time Search; Traditional Search; Social Network
期刊名称:
《Hans Journal of Data Mining》, Vol.3 No.2, 2013-04-30
摘要:
随着社交网络的兴起，网民对信息资讯的速度和实时性提出了更高的要求。传统搜索引擎通过费时的网络爬虫抓取网页，建立索引，这已远不能满足用户的需求。相比之下，实时搜索能直接从网络捕获数据流，从而更迅速地满足用户对实时信息的需求。目前国内外已经出现了一些实时搜索引擎，如美国的OneRiot、Google、Collecta和Scoopler等，它们通过抓取Twitter、Facebook、Digg等社交网络上用户随时发布的海量信息，给人们提供最新的搜索内容。
With the rise of social network, Internet users have put forward higher request on the speed and real-time for information. Through the time-consuming web crawler, traditional search engine grab the web page, and establish the index, which can not meet the users’ needs. In contrast, the real-time search can capture the data flow directly from the network, thus it meets the needs of the users for real-time information more quickly. Some real-time search engines have already appeared at home and abroad, such as the United States OneRiot, Google, Collecta and Scoopler, etc., which provide people with the latest search content through grabbing the mass information released by the users on Twitter, Facebook, Digg, etc. at any time.