Workshop Topics
Possible topics of the workshop include (but are not limited to):
* Social network analysis
* Bibliometrics
* Community discovery
* Personalization for search and for social interaction
* Recommender systems
* Web mining algorithms
* Applications of social network analysis
* Mining (Collaborative) Tagging Systems (blogs, wikis, etc.)
* Mining social data for multimedia information retrieval
* Opinion mining
Web search engines have changed our lives - enabling instant access to information about subjects that are both deeply important to us, as well as passing whims. The search engines that provide answers to our search queries also log those queries, in order to improve their algorithms. Academic research on search queries has shown that they can provide valuable information on diverse topics including word and phrase similarity, topical seasonality and may even have potential for sociology, as well as providing a barometer of the popularity of many subjects. At the same time, individuals are rightly concerned about what the consequences of accidental leaking or deliberate sharing of this information may mean for their privacy. In this talk I will cover the applications which have benefited from mining query logs, the risks that privacy can be breached by sharing query logs, and current algorithms for mining logs in a way to prevent privacy breaches.
Data Mining, Analytics, and Databases
Databases are the workhorse of the enterprise today. Searching through databases and finding useful information has become a big computational challenge. Researchers from academia and Microsoft, Oracle, SAP, and many other corporations are looking to CUDA-enabled GPUs to find a scalable solution.
Platform for sharing and evaluation of intelligent algorithms. Data mining data, experiments, datasets, performance analysis, data repository, challenges. Research and applications, prediction. Data mining and machine learning
Twitter wird sein frisch eingekauftes Echtzeit-DV-System Storm als Open Source veröffentlichen. Damit wird die Technik für die Parallelisierung von Datenbankabfragen für alle verfügbar.
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)
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)