Mining Search Queries
- Type
- Audio
- Tags
- data mining
- Event
- Chaos Communication Congress 23th (23C3) 2006
- Indexed on
- Mar 27, 2013
- URL
- http://dewy.fem.tu-ilmenau.de/CCC/23C3/audio/23C3-1498-en-mining_aol_search_queries.mp3
- File name
- 23C3-1498-en-mining_aol_search_queries.mp3
- File size
- 45.0 MB
- MD5
- 14b62d13f624a1ed63ecfe2fbe8cbb9f
- SHA1
- 6ae6477f35d215b0b12a2f44a8bf585cf806be40
AOL recently published over 34M weakly anonymized search queries from their users by intension. This lecture gives an overview on the results of an extensive statistical analysis and data mining procedure on this dataset. Thereby, a methodology for frequency analysis, search trend mining, topic detection and even user profiling and identification will be presented. The lecture will give an overview on knowledge discovery techniques on a sample dataset of real search queries released by AOL. Although AOL anonymized the records by hiding the user name of the sender, this lecture will show how much knowledge you can already gain out of those web logs. The lecture targets on showing the dangers of progressional data collection and aggregation, particulary of rich user profile mining from search query logs.
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