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现代图书情报技术  2014, Vol. 30 Issue (6): 94-99    DOI: 10.11925/infotech.1003-3513.2014.06.11
  应用实践 本期目录 | 过刊浏览 | 高级检索 |
在线群体创新中的图片推荐方法研究
张晓燕, 张朋柱, 李嘉, 刘景方
上海交通大学安泰经济与管理学院 上海 200052
Research on Picture Recommendation for Creativity Support System
Zhang Xiaoyan, Zhang Pengzhu, Li Jia, Liu Jingfang
Antai College of Economics & Management, Shanghai Jiaotong University, Shanghai 200052, China
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摘要 

[目的]基于相关性、多样性原则, 利用图片推荐的方法刺激群体创新。[应用背景]在群体创意的环境中提供刺激信息刺激群体思维。[方法]基于文本分词、网页分析以及余弦相似度算法, 建立图片推荐系统的模型, 提出最大差异化算法, 向正在创意的群体推荐多样性高的图片信息。[结果]通过实验研究, 证明采用最大差异化算法的图片推荐系统对于群体创新绩效的促进作用。[局限]图片最大差异化算法中的相关性和差异性主要基于图片的描述信息, 与图片本身的内容有一定的差异, 因此基于图片描述信息的最大差异化算法存在局限性。[结论]在群体创新过程中, 通过不断推荐差异化图片的方法能够提高群体创意的绩效。

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张朋柱
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关键词 在线群体研讨群体支持系统图片推荐系统群体创意    
Abstract

[Objective]Base on the principle of diversity and correlation, stimulate the group creativity by recommending pictures. [Context]The application context is group idea generation environment. [Methods] Base on text segmentation, webpage analysis technique and cosine similarity algorithm, the paper establishes a model of picture recommending system and raises Max Difference Algorithm (MDA) to select pictures for groups which in the process of creativity. [Results] This research proves the positive effect of picture recommendation system to group idea generation by an experiment method and proves the usability and accessibility of the system by survey. [Limitations]The Max Difference Algorithm is based on the text information around the pictures, and this information is often in difference with the pictures' content, so there are limitations on the MDA.[Conclusions] In the group idea generation process, group creativity performance can be improved by recommending pictures.

Key wordsOnline group discussion    Group support system    Picture recommendation    Group idea generation
收稿日期: 2013-10-24     
:  C931.6  
基金资助:

本文系国家自然科学基金面上项目“面向网络化创新外包的任务–人才在线匹配研究”(项目编号:71171131)、国家自然科学基金面上项目“理论引导的在线电子健康决策平台设计研究: 基于人机交互的视角”(项目编号:71371005)和国家自然科学基金项目“我国电子政务标准的产生机制及采纳扩散机制”(项目编号: 71103021)的研究成果之一。

通讯作者: 张晓燕E-mail:zzlveofer@hotmail.com     E-mail: zzlveofer@hotmail.com
作者简介: 作者贡献声明:张晓燕:论文思路设计、系统开发、实验、数据分析及论文撰写;张朋柱:提出研究思路,设计研究方案;李嘉:指导实验设计和实验分析,论文修订;刘景方:数据分析。
引用本文:   
张晓燕, 张朋柱, 李嘉, 刘景方. 在线群体创新中的图片推荐方法研究[J]. 现代图书情报技术, 2014, 30(6): 94-99.
Zhang Xiaoyan, Zhang Pengzhu, Li Jia, Liu Jingfang. Research on Picture Recommendation for Creativity Support System. New Technology of Library and Information Service, DOI:10.11925/infotech.1003-3513.2014.06.11.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2014.06.11

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