Name
Abstract | ||
|---|---|---|
Computational advertising is an emerging scientific discipline, at the intersection of large scale search and text analysis, information retrieval, statistical modeling, machine learning, optimization, and microeconomics. The central challenge of computational advertising is to find the "best match" between a given user in a given context and a suitable advertisement. The context could be a user entering a query in a search engine ("sponsored search"), a user reading a web page ("content match" and "display ads"), a user conversing on a cell phone ("mobile advertising"), and so on. The information about the user can vary from scarily detailed to practically nil. The number of potential advertisements might be in the billions. Thus, depending on the definition of "best match" this challenge leads to a variety of massive optimization and search problems, with complicated constraints. The main part of this talk will give an introduction to computational advertising and present some illustrative research. In the second part we will discuss connections to recommender systems and present a couple of open problems of potential interest to both communities. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1145/1454008.1454009 | RecSys |
Keywords | Field | DocType |
recommender system,mobile advertising,search engine,large scale search,content match,central challenge,search problem,information retrieval,recommender systems,computational advertising,massive optimization,sponsored search,main part,machine learning,web pages,text analysis,statistical model | Web page,Computer science,Computational advertising,Online advertising,Phone,Artificial intelligence,Mobile advertising,Recommender system,World Wide Web,Search engine,Information retrieval,Statistical model,Machine learning | Conference |
Citations | PageRank | References |
13 | 0.84 | 1 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrei Broder | 1 | 7357 | 920.20 |