Query log data for ad targeting
A WWW2006 paper out of Microsoft Research, "Finding Advertising Keywords on Web Pages" (PDF), claims that query log data is particularly useful for ad targeting.
Specifically, the researchers extracted from MSN query logs the keywords some people used to find a given page. They tested using that as one of many features for ad targeting. In their results, it was one of the most effective features.
Very interesting. It has always been harder to target ads to content than to search results because intent is much less clear.
By using the query log data in this way, the researchers were effectively using the intent of the searchers that arrived at the page as a proxy for the intent of everyone who arrived at the page.
Microformats are small and gentle syntactic touchups for your web pages.They have one major purpose: to make your data readable by both man and machine...The machine-readable-data (and thus the microformat) concept is not new; it has a very recent fo
Powerful Search Engine designed for Document Management, Competitive Intelligence, Press Analysis and Text Mining, Web Mining, Knowledge Discovery, Strategic Watch...Has Report Writer, Web Spider, Publisher, more...
Regarding links: back about 12 years ago we built a software framework in the (then new) Java language named "Roku". Our ontology in Roku (Japanese for 'six') broke everything into one of six categories (Who, What, When, Where, Why and How).
T. Groza, S. Handschuh, K. Möller, und S. Decker. Proceedings of the 5th European Semantic Web Conference, Berlin, Heidelberg, Springer Verlag, (Juni 2008)
F. Dau. Proceedings of the 19th International Conference on Conceptual Structures (ICCS 2011), Volume 6828 von Lecture Notes in Computer Science, Seite 1-18. Springer, (2011)
R. Baeza-Yates, und A. Tiberi. KDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, Seite 76--85. New York, NY, USA, ACM, (2007)
M. Atzmueller, und D. Seipel. Proc. 18th International Conference on Applications of Declarative Programming and Knowledge Management, accepted, (2008)
M. Atzmueller, und F. Puppe. Proc. 15th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2006), 4248, Seite 318--325. (2006)
M. Atzmueller, F. Puppe, und H. Buscher. Proc. 10th International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-2005), Seite 46--51. Aberdeen, Scotland, (2005)
M. Atzmueller, J. Baumeister, und F. Puppe. Artificial Intelligence in Medicine. Special Issue on Intelligent Data Analysis in Medicine, 37 (1):
19--30(2006)
M. Atzmueller, J. Baumeister, und F. Puppe. Medical Data Analysis, Proc. 4th Intl. Symposium on Medical Data Analysis (ISMDA 2003), LNCS 2868, Seite 23-30. (2003)
R. Zgheib, A. Nicola, M. Villani, E. Conchon, und R. Bastide. 2017 IEEE 26th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), Seite 284-289. (Juni 2017)
A. Dridi, S. Sassi, und S. Faiz. 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA), Seite 1421-1428. (Oktober 2017)
B. Berendt, A. Hotho, und G. Stumme. Web Semantics: Science, Services and Agents on the World Wide Web, 8 (2-3):
95 - 96(2010)Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0; The Future of Knowledge Dissemination: The Elsevier Grand Challenge for the Life Sciences.
M. Atzmueller, F. Puppe, und H. Buscher. Proc. 10th International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-2005), Seite 46--51. Aberdeen, Scotland, (2005)
J. Baumeister, M. Atzmueller, und F. Puppe. Advances in Case-Based Reasoning, Volume 2416 von LNAI, Seite 28-42. (2002)Proc. 6th European Conference on Case-Based Reasoning (ECCBR 2002).
S. Tramp, P. Frischmuth, T. Ermilov, und S. Auer. Proceedings of the EKAW 2010 - Knowledge Engineering and Knowledge Management by the Masses; 11th October-15th October 2010 - Lisbon, Portugal, Volume 6317 von Lecture Notes in Artificial Intelligence, Seite 135--149. Berlin / Heidelberg, Springer, (Oktober 2010)
B. Berendt, A. Hotho, und G. Stumme. Web Semantics: Science, Services and Agents on the World Wide Web, 8 (2-3):
95 - 96(2010)Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0; The Future of Knowledge Dissemination: The Elsevier Grand Challenge for the Life Sciences.
M. Atzmueller, S. Beer, und F. Puppe. Proc. 22nd International Florida Artificial Intelligence Research Society Conference (FLAIRS), accepted, Seite 372-377. AAAI Press, (2009)
B. Berendt, A. Hotho, und G. Stumme. Web Semantics: Science, Services and Agents on the World Wide Web, 8 (2-3):
95 - 96(2010)Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0; The Future of Knowledge Dissemination: The Elsevier Grand Challenge for the Life Sciences.
F. Suchanek, G. Kasneci, und G. Weikum. Proceedings of the 16th international conference on World Wide Web, Seite 697--706. New York, NY, USA, ACM, (2007)
M. Atzmueller, J. Baumeister, und F. Puppe. Medical Data Analysis, Proc. 4th Intl. Symposium on Medical Data Analysis (ISMDA 2003), LNCS 2868, Seite 23-30. (2003)
J. Choi, A. Khlif, und E. Epure. Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA), Seite 23--27. Online, Association for Computational Linguistics, (2020)
M. Atzmueller, J. Baumeister, und F. Puppe. Artificial Intelligence in Medicine. Special Issue on Intelligent Data Analysis in Medicine, 37 (1):
19--30(2006)
C. Seitz, C. Legat, und J. Neidig. Workshops Proceedings of the 5th International Conference on Intelligent Environments, Volume 4 von Ambient Intelligence and Smart Environments, Seite 51--57. Amsterdam, IOS Press, (2009)