基于SA模型的数字图书馆个性化搜索

摘要

随着信息技术的飞速发展，数字图书馆的信息正在已不可思议的速度增加，从而导致信息超负载。个性化搜索致力于跟踪大量搜索结果来满足每个用户的需求。本文提出一种基于激活扩散模型（SA）计算数据来重新对搜索结果进行分类的方法。扩散激活被应用于领域本体，从而建立一种新型的borrowintent的关系。%With the rapid development of information technology, digital libraries of information is already incredible speed increase, leading to information overload.Personalized Search is committed to tracking a large number of search results to meet the needs of each user.This paper presents a model based on spreading activation（SA）calculations to re-sort the search results means.Diffusion activation domain ontology is used to establish a new borrowintent relationship.