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In sponsored search advertising, keywords serve as an essential bridgelinking advertisers, search users and search engines. Advertisers have to dealwith a series of keyword decisions throughout the entire lifecycle of searchadvertising campaigns. This paper proposes a multi-level and closed-formcomputational framework for keyword optimization (MKOF) to support variouskeyword decisions. Based on this framework, we develop correspondingoptimization strategies for keyword targeting, keyword assignment and keywordgrouping at different levels (e.g., market, campaign and adgroup). With tworeal-world datasets obtained from past search advertising campaigns, we conductcomputational experiments to evaluate our keyword optimization framework andinstantiated strategies. Experimental results show that our method can approachthe optimal solution in a steady way, and it outperforms two baseline keywordstrategies commonly used in practice. The proposed MKOF framework also providesa valid experimental environment to implement and assess various keywordstrategies in sponsored search advertising.

Keyword Optimization in Sponsored Search Advertising: A Multi-Level Computational Framework