摘要: 对计算广告研究中的计价模型和匹配算法及模型进行综述,分别从检索词匹配精度、语义情景和用户点击反馈等方面对Cosine算法、Okapi BM25算法、特征学习算法、分层学习模型和Multinomial统计语言模型等进行比较分析和优缺点总结,并提出可行的改进 方向。
关键词:
赞助搜索,
内容匹配,
信息检索,
机器学习,
在线学习
Abstract: This paper conducts a survey of pricing models, relevance match algorithms, and effective statistical models for computing advertising, analyzes and compares these approaches, like Cosine, Okapi BM25, feature learning, hierarchy-learning and Multinomial language model, and conclusively points out the feasible improvement and future of research in this field.
Key words:
sponsored search,
content match,
information retrieval,
machine learning,
online learning
中图分类号:
郭庆涛, 郑滔. 计算广告的匹配算法综述[J]. 计算机工程, 2011, 37(7): 222-224,233.
GUO Qiang-Chao, ZHENG Tao. Match Algorithms Survey of Computing Advertising[J]. Computer Engineering, 2011, 37(7): 222-224,233.