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

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

CLC Number: 

• TP18