Lexical graphs for improved contextual Ad recommendation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5478 LNCS, Issue , 2009, Pages 216-227

  Papadopoulos, Symeon ^a   Menemenis, Fotis ^a   Kompatsiaris, Yiannis ^a   Bratu, Ben ^b  

^a INFORMATICS AND TELEMATICS INSTITUTE   (Greece)

^b Motorola Labs   (France)

Author keywords

Content targeted advertising; Lexical graphs; Online advertising; Vocabulary impedance

Indexed keywords

CONTENT SIMILARITY; CONTENT-TARGETED ADVERTISING; EXPERIMENTAL STUDIES; LEXICAL GRAPHS; ONLINE ADVERTISING; REVENUE GROWTH; VOCABULARY IMPEDANCE; WEB CORPORA; WEB PAGE;

INFORMATION RETRIEVAL SYSTEMS; INFORMATION SERVICES; WORLD WIDE WEB;

INFORMATION RETRIEVAL;

EID: 67650706587     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-00958-7_21     Document Type: Conference Paper

References (10)

1. Richardson, M., Dominowska, E., Ragno, R.: Predicting clicks: estimating the clickthrough rate for new ads. In: Proceedings of the 16th international conference on World Wide Web (WWW 2007), pp. 521-530. ACM, New York (2007) (Pubitemid 47582281)
2. Ribeiro-Neto, B., Cristo, M., Golgher, B.G., de Moura, E.S.: Impedance Coupling in Content-targeted Advertising. In: Proceedings of the 28th annual international ACM SIGIR conference (SIGIR 2005), pp. 496-503. ACM, New York (2005)
3. Lacerda, A., Cristo, M., Goncalves, M.A., Fan, W., Ziviani, N., Ribeiro-Neto, B.: Learning to advertise. In: Proceedings of the 29th annual international ACM SIGIR conference (SIGIR 2006), pp. 549-556. ACM, New York (2006)
4. Murdock, V., Ciaramita, M., Plachouras, V.: A noisy-channel approach to contextual advertising. In: Proceedings of the 1stWorkshop on Data Mining and Audience intelligence for Advertising (ADKDD 2007), pp. 21-27. ACM, New York (2007)
5. Yih,W., Goodman, J., Carvalho, V.R.: Finding advertising keywords on web pages. In: Proceedings of the 15th international conference on World Wide Web (WWW 2006), New York, pp. 213-222 (2006) (Pubitemid 46946612)
6. Mishne, G., de Rijke, M.: Language model mixtures for contextual ad placement in personal blogs. In: Salakoski, T., Ginter, F., Pyysalo, S., Pahikkala, T. (eds.) FinTAL 2006. LNCS, vol.4139, pp. 435-446. Springer, Heidelberg (2006)
7. Broder, A., Fontoura, M., Josifovski, V., Riedel, L.: A semantic approach to contextual advertising. In: Proceedings of the 30th annual international ACM SIGIR conference (SIGIR 2007), pp. 559-566. ACM, New York (2007) (Pubitemid 350165004)
8. Widdows, D., Dorow, B.: A graph model for unsupervised lexical acquisition. In: Proceedings of the 19th international conference on Computational Linguistics, pp. 1-7. Association for Computational Linguistics, Morristown (2002)
9. Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. Communications of the ACM 18(11), 613-620 (1975)
10. Cohen, J.: A coefficient of agreement for nominal scales. Educational and Psychological Measurement 20(1), 37-46 (1960)