摘要
提出并研究、实现了基于用户偏好的垂直搜索算法(PVSA)。以领域特征为基本出发点,PVSA借助领域主题偏好向量、领域元数据权重因子、检索名词差异化、行业词典库更新等4项策略,有效地挖掘、表征用户的领域个性化偏好,以此为基础构建基于用户偏好的垂直搜索算法。实验结果表明了PVSA算法的有效性和可行性。
Personalized search and vertical search are receiving more and more attention of users. User preference-based vertical search algorithm (PVSA) is proposed in this paper. By focusing on domain characteristics, PVSA uses domain topic preference vector, domain metadata weight factors, the strategy of distinguishing weights of input terms, and industry lexicon update to mine different domain preferences of different users. Experimental results show that the proposed algorithm is feasible and effective in mining users' personal preferences.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2010年第1期91-96,共6页
Journal of University of Electronic Science and Technology of China
基金
国家973重点基础研究发展规划(2007CB307100)
国家自然科学基金(60872051)
国家科技支撑计划重大项目(2006BAH02A11)
北京市教委产学研项目(zh100130525)
关键词
词库
差异化
领域主题偏好向量
元数据权重因子
用户偏好
dictionaries
differentiation
domain topic preference vector
metadata weight factors
user's preferences