|
|
Modeling Research of Users Dynamic Interests Based on Ontology and Folksonomy |
Li Yuanyuan, Li Xuhui |
School of Information Management, Wuhan University, Wuhan 430072 |
|
|
Abstract Web 2.0 application technologies, such as blog, instant messaging, social network, community sharing, and Folksonomy, enable the combination of users, information, and resources to form a closely related web network. In recent times, there have been limited research studies that apply ontology to analyze the dynamic interests of the users of social tags. Therefore, a platform’s requirements related to an accurate understanding of its users’ interests are not fulfilled. Our study discusses the construction method of interest model from this standpoint. The ontology of interest labels for Douban readers is constructed in this study on the basis of restriction rules and relationship definitions of words in the Chinese Classification Thesaurus and Chinese Library Classification. According to the index of reproduction, coverage, and calorific rate, the interest intensity and stability of tags are predicted, and the expression form of interest is determined. The initial interest model is then constructed, and the corresponding renewal process of interest nodes is proposed. The user’s interest model combined with ontology and its update process have improved the expression depth and width of user interests to a certain extent. Thus, this work demonstrates a higher scientific reference significance in the applicability of resource recommendation, retrieval, and other applications.
|
Received: 16 October 2019
|
|
|
|
1 潘淑如. 社会化标签系统中基于本体的个性化信息推荐模型探究[J]. 图书馆学研究, 2014(21): 77-80, 37. 2 扈维, 张尧学, 周悦芝. 基于社会化标注的用户兴趣挖掘[J]. 清华大学学报(自然科学版), 2014, 54(4): 502-507. 3 夏宁霞, 苏一丹, 覃华, 等. 社会化标签系统中个性化的用户建模方法[J]. 计算机应用, 2011, 31(6): 1667-1670. 4 秦勤. 基于用户标注兴趣模型的个性化信息推荐研究[D]. 太原: 山西医科大学, 2018. 5 WuB X, XiaoJ, ChenJ M. Friend recommendation by user similarity graph based on interest in social tagging systems[C]// Proceedings of the International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. Cham: Springer, 2015, 9227: 375-386. 6 XuZ H, RuL, XiangL, et al. Discovering user interest on Twitter with a modified author-topic model[C]// Proceedings of the IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology. New York: IEEE, 2011: 422-429. 7 易明, 毛进, 邓卫华. 基于社会化标签网络的细粒度用户兴趣建模[J]. 现代图书情报技术, 2011(4): 35-41. 8 易明, 邓卫华, 徐佳. 社会化标签系统中基于组合策略的个性化知识推荐研究[J]. 情报科学, 2011, 29(7): 1093-1097. 9 易明, 操玉杰, 沈劲枝, 等. 社会化标签系统中基于密度聚类的Web用户兴趣建模方法[J]. 情报学报, 2011, 30(1): 37-43. 10 张艳梅, 王璐. 适应用户兴趣变化的社会化标签推荐算法研究[J]. 计算机工程, 2014, 40(11): 318-321. 11 孙雨生. 国内基于本体的用户兴趣建模研究进展(下)——模型管理[J]. 情报理论与实践, 2015, 38(1): 139-144. 12 陈一峰, 赵恒凯, 余小清, 等. 基于本体的用户兴趣模型构建研究[J]. 计算机工程, 2010, 36(21): 46-48, 51. 13 范玉全, 陈跃新. 基于本体的用户兴趣模型的更新方法[J]. 计算机光盘软件与应用, 2013, 16(7): 22-23, 35. 14 李志隆, 王道平, 关忠兴. 基于领域本体的用户兴趣模型构建方法研究[J]. 情报科学, 2015, 33(11): 69-73. 15 谢梦瑶. 社会化标注中用户动态兴趣主题挖掘[D]. 杭州: 浙江理工大学, 2017. |
|
|
|