Abstract
We propose a model of coverage patterns and a methodology to extract coverage patterns from transactional databases. We have discussed how the coverage patterns are useful by considering the problem of banner advertisements placement in e-commerce web sites. Normally, advertiser expects that the banner advertisement should be displayed to a certain percentage of web site visitors. On the other hand, to generate more revenue for a given web site, the publisher has to meet the coverage demands of several advertisers by providing appropriate sets of web pages. Given web pages of a web site, a coverage pattern is a set of pages visited by a certain percentage of visitors. The coverage patterns discovered from click-stream data could help the publisher in meeting the demands of several advertisers. The efficiency and advantages of the proposed approach is shown by conducting experiments on real world click-stream data sets.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
References
Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: VLDB 1994: Proceedings of the 20th International Conference on Very Large Data Bases, pp. 487–499. Morgan Kaufmann Publishers Inc. (1994)
Chvatal, V.: A greedy heuristic for the set-covering problem. Mathematics of Operations Research, 233–235 (1979)
Garey, M.R., Johnson, D.S., Stockmeyer, L.: Some simplified np-complete problems. In: Proceedings of the Sixth Annual ACM Symposium on Theory of Computing, STOC 1974, pp. 47–63. ACM (1974)
Venetis, P., Koutrika, G., Garcia-Molina, H.: On the selection of tags for tag clouds. In: Proceedings of the Fourth ACM International Conference on Web Search and Data Mining, WSDM 2011, pp. 835–844. ACM (2011)
Bonchi, F., Castillo, C., Donato, D., Gionis, A.: Topical query decomposition. In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008, pp. 52–60. ACM (2008)
Amiri, A., Menon, S.: Efficient scheduling of internet banner advertisements. ACM Trans. Internet Technol. 3(4), 334–346 (2003)
Ghosh, A., Rubinstein, B.I., Vassilvitskii, S., Zinkevich, M.: Adaptive bidding for display advertising. In: WWW 2009: Proceedings of the 18th International Conference on World Wide Web, pp. 251–260. ACM (2009)
Wu, X., Bolivar, A.: Keyword extraction for contextual advertisement. In: WWW 2008: Proceeding of the 17th International Conference on World Wide Web, pp. 1195–1196. ACM (2008)
Chakrabarti, D., Agarwal, D., Josifovski, V.: Contextual advertising by combining relevance with click feedback. In: WWW 2008: Proceeding of the 17th International Conference on World Wide Web, pp. 417–426. ACM (2008)
Alaei, S., Arcaute, E., Khuller, S., Ma, W., Malekian, A., Tomlin, J.: Online allocation of display advertisements subject to advanced sales contracts. In: ADKDD 2009: Proceedings of the Third International Workshop on Data Mining and Audience Intelligence for Advertising, pp. 69–77. ACM (2009)
Sripada, B., Reddy, P.K., Kiran, R.U.: Coverage patterns for efficient banner advertisement placement. In: WWW (Companion Volume), pp. 131–132 (2011)
Liu, B., Hsu, W., Ma, Y.: Mining association rules with multiple minimum supports. In: KDD 1999: Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 337–341. ACM (1999)
Han, J., Kamber, M.: Data mining: concepts and techniques. Morgan Kaufmann (2006)
Fimi: Frequent itemset mining implementations repository (July 2010), http://fimi.cs.helsinki.fi/
Frank, A., Asuncion, A.: UCI machine learning repository (2010), http://archive.ics.uci.edu/ml
Agrawal, R., Imieliński, T., Swami, A.: Mining association rules between sets of items in large databases. In: Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, SIGMOD 1993, pp. 207–216. ACM (1993)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Srinivas, P.G., Reddy, P.K., Bhargav, S., Kiran, R.U., Kumar, D.S. (2012). Discovering Coverage Patterns for Banner Advertisement Placement. In: Tan, PN., Chawla, S., Ho, C.K., Bailey, J. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2012. Lecture Notes in Computer Science(), vol 7302. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30220-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-30220-6_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30219-0
Online ISBN: 978-3-642-30220-6
eBook Packages: Computer ScienceComputer Science (R0)