Internet and Operations Research

MIT is holding a conference on Operations Research and the Internet at the end of May, and it looks excellent! They have some very smart people, like David Williamson of Cornell and Meredith Goldsmith of Google, speaking and their topics look very much like strong operations research: no fluff! Here is Williamson’s abstract to give a flavor for the conference:

An Adaptive Algorithm for Selecting Profitable Keywords for Search-Based Advertising ServicesIncreases in online search activities have spurred the growth of search-based advertising services offered by search engines. These services enable companies to promote their products to consumers based on their search queries. In most search-based advertising services, a company selects a set of keywords, determines a bid price for each keyword, and designates an ad associated with each selected keyword. When a consumer searches for one of the selected keywords, search engines then display the ads associated with the highest bids for that keyword on the search result page. A company whose ad is displayed pays the search engine only when the consumer clicks on the ad. With millions of available keywords and a highly uncertain clickthru rate associated with the ad for each keyword, identifying the most effective set of keywords and determining corresponding bid prices becomes challenging for companies wishing to promote their goods and services via search-based advertising.

Motivated by these challenges, we formulate a model of keyword selection in search-based advertising services. We develop an algorithm that adaptively identifies the set of keywords to bid on based on historical performance. The algorithm prioritizes keywords based on a prefix ordering — sorting of keywords in a descending order of profit-to-cost ratio. We show that the average expected profit generated by the algorithm converges to near-optimal profits. Furthermore, the convergence rate is independent of the number of keywords and scales gracefully with the problem’s parameters. Extensive numerical simulations show that our algorithm outperforms existing methods, increasing profits by about 7%. We also explore extensions to current search-based advertising services and indicate how to adapt our algorithm to these settings.

This is joint work with Paat Rusmevichientong (Cornell).

Looks like a very good conference.

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