A pre-relational databases datamodel. "Preceeded" by the relational model since the flexibility of this makes it hard to work with. Now re-invented in RDF :)
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.
Free Downloads and Links - ODBMS.ORG was created to serve faculty and students at educational and research institutions as well as OO software developers in the open source community or at commercial companies.
Wir sind im Jahr 2012 angekommen - deutsche Verkehrsunternehmen aber noch nicht. Weder die Unternehmen noch die Politik haben es verstanden, welche Innovationskraft tausende freiwillige Entwickler_innen haben, um völlig neue Verkehrsapps oder Mobilitätskonzepte zu entwickeln - für Menschen, die viel reisen oder täglich pendeln, denen wegen Rollstuhl oder Gehhilfe Barrieren in den Weg gelegt werden, oder einfach mehr erwarten, als nur eine langweilige Fahrplanauskunft. Deshalb nehmen wir das jetzt in die Hand und werden alle Fahrpläne veröffentlichen - als Start für neue Innovation ohne Erlaubnis.
Berlin wird leiser: aktiv gegen Verkehrslärm. - Die Senatsverwaltung für Stadtentwicklung und Umwelt Berlin will ihre Bürger an der Erarbeitung des Lärmaktionsplans beteiligen. Alle Bürgerinnen und Bürger können mitteilen, wo es ihnen in Berlin zu laut ist und welche Maßnahmen Abhilfe schaffen könnten. Auf dieser Basis erarbeitet die Stadt Maßnahmen, wie Berlin leiser werden kann.
The Net Data Directory collects and shares information on different sources of data about the Internet. For more about the project, see our about page. To get started, use the search box below, or check out our quick start guide.
Wir fordern deshalb die Einhaltung folgender Grundprinzipien:
die Funktion von Informationssystemen stärker zu dezentralisieren;
informationelle Selbstbestimmung und Partizipation zu unterstützen;
Transparenz für eine erhöhte Vertrauenswürdigkeit zu verbessern;
Informationsverzerrungen und -verschmutzung zu reduzieren;
von den Nutzern gesteuerte Informationsfilter zu ermöglichen;
gesellschaftliche und ökonomische Vielfalt zu fördern;
die Fähigkeit technischer Systeme zur Zusammenarbeit zu verbessern;
digitale Assistenten und Koordinationswerkzeuge zu erstellen;
kollektive Intelligenz zu unterstützen; und
die Mündigkeit der Bürger in der digitalen Welt zu fördern – eine "digitale Aufklärung".
Map-Reduce is on its way out. But we shouldn’t measure its importance in the number of bytes it crunches, but the fundamental shift in data processing architectures it helped popularise.
The files below contain XML (and only XML) for all the articles in the PMC open access subset. These files were created for users who need PMC XML for data mining and processing purposes, but do not need PDFs, images, or supplementary data.
S. Tramp, P. Frischmuth, T. Ermilov, and S. Auer. Proceedings of the EKAW 2010 - Knowledge Engineering and Knowledge Management by the Masses; 11th October-15th October 2010 - Lisbon, Portugal, volume 6317 of Lecture Notes in Artificial Intelligence, page 135--149. Berlin / Heidelberg, Springer, (October 2010)
M. Atzmueller, D. Benz, A. Hotho, and G. Stumme (Eds.) Technical report (KIS), 2010-10 Department of Electrical Engineering/Computer Science, Kassel University, (2010)
B. Berendt, A. Hotho, and 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.
B. Berendt, A. Hotho, and 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.
A. Brew, D. Greene, and P. Cunningham. Proceedings of the 19th European Conference on Artificial Intelligence, volume 215 of Frontiers in Artificial Intelligence and Applications, page 145--150. Amsterdam, The Netherlands, The Netherlands, IOS Press, (2010)
B. Martins, H. Manguinhas, and J. Borbinha. Proceedings of the International Conference on Semantic Computing, page 1--9. IEEE Computer Society, (August 2008)
F. Suchanek, G. Kasneci, and G. Weikum. Proceedings of the 16th international conference on World Wide Web, page 697--706. New York, NY, USA, ACM, (2007)
A. Clauset, C. Shalizi, and M. Newman. (2007)cite arxiv:0706.1062Comment: 43 pages, 11 figures, 7 tables, 4 appendices; code available at http://www.santafe.edu/~aaronc/powerlaws/.
N. Tatti, T. Mielikainen, A. Gionis, and H. Mannila. Proceedings of the Sixth IEEE International Conference on Data Mining (ICDM 2006), page 603--612. IEEE, (December 2006)
T. Joachims, L. Granka, B. Pan, H. Hembrooke, and G. Gay. SIGIR '05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, page 154--161. New York, NY, USA, ACM, (2005)
G. Gottlob, C. Koch, R. Baumgartner, M. Herzog, and S. Flesca. Proceedings of the Twenty-third ACM SIGACT-SIGMOD-SIGART Symposium
on Principles of Database Systems, June 14-16, 2004, Paris, France, page 1-12. ACM, (2004)
A. Hotho, S. Staab, and G. Stumme. Proceedings of the 2003 IEEE International Conference on Data Mining, page 541-544 (Poster. Melbourne, Florida, IEEE Computer Society, (November 2003)
J. Lin, E. Keogh, S. Lonardi, and B. Chiu. Proceedings of the 8th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, page 2--11. New York, NY, USA, ACM, (2003)
A. Arasu, and H. Garcia-Molina. Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, San Diego, California, USA, June 9-12, 2003, page 337-348. ACM, (2003)
T. Joachims. Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, page 133--142. New York, NY, USA, ACM, (2002)
M. Banko, and E. Brill. ACL '01: Proceedings of the 39th Annual Meeting on Association for Computational Linguistics, page 26--33. Morristown, NJ, USA, Association for Computational Linguistics, (2001)
A. Maedche, A. Hotho, and M. Wiese. Data Warehousing and Knowledge Discovery, Second International Conference, DaWaK 2000, London, UK, volume 1874 of LNCS, page 258-264. Springer, (2000)
S. Simoff. Proceedings of the MDKM/KDD2000 Workshop on
Multimedia Data Mining, page 104--109. www.cs.ualberta.ca/~zaiane/mdm\_kdd2000/mdm00-15.pdf, (2000)
U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth. Advances in knowledge discovery and data mining, American Association for Artificial Intelligence, Menlo Park, CA, USA, (1996)
U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth. chapter From data mining to knowledge discovery: an overview, American Association for Artificial Intelligence, Menlo Park, CA, USA, (1996)