基于用户人格特征的信息过滤模型  

The Reseach on Personality-Based Information Filtering Model

作　　者：唐晓玲[1] 

机构地区：[1]四川外语学院图书馆,重庆400031

出　　处：《图书情报工作》2009年第10期59-62,共4页Library and Information Service

摘　　要：将用户人格融入到信息推荐服务的过滤过程中,构建基于用户人格特征的信息过滤模型。运用凯尔西人格理论、概率论、人格分布理论以及统计推理,完成模型中的分段、学习、分类和过滤4个环节。根据用户模型或用户提供的关键词、人格特征为用户过滤或推荐信息单元,旨在更好地为用户提供个性化的信息服务。This paper incorporates human personality into the filtering process of information recommendation service, and constructs a Personality-Based Information Filtering Model （PBIFM）. The purpose is to devise a new filtering mechanism, which addresses segmentation, learning, classification, and filtering of the model, based on Keirsey＇ s personality theory, probability theory, the distributions theory of personality, and statistical reasoning. By presenting information units that are consistent with user profiles or keywords and users personality provided by users, the personlized information service will be better.

关 键 词：信息过滤 凯尔西人格理论 概率论 个性化信息服务 

分 类 号：G203[文化科学—传播学]