Title :
The MIDAS data-mining project at Stanford
Author :
Ullman, Jeffrey D.
Author_Institution :
Dept. of Comput. Sci., Stanford Univ., CA, USA
Abstract :
The article summarizes recent research into data-mining techniques that are in progress at Stanford: 1. The Google search engine: beating Yahoo et al. at their own game. 2. Query flocks: generalizing association rules/market baskets in a query precompiler that uses a relational DBMS effectively. 3. Synthesizing knowledge from the Web: exploiting the Web´s redundancy to extract data automatically. 4. Detecting low-frequency events: unlike marketing, where you only care about items that lots of people buy, extracting intelligence from text usually requires looking for a small number of unexpected juxtapositions of terms
Keywords :
data mining; information resources; query processing; relational databases; research initiatives; search engines; Google search engine; MIDAS data mining project; Stanford University; Web redundancy; association rule generalisation; automatic data extraction; knowledge synthesis; low-frequency event detection; market basket generalisation; query flocks; query precompiler; relational DBMS; term juxtapositions; Computer science; Data mining; Databases; Event detection; Filters; Joining processes; Large-scale systems; Marketing and sales; Plagiarism; Search engines;
Conference_Titel :
Database Engineering and Applications, 1999. IDEAS '99. International Symposium Proceedings
Conference_Location :
Montreal, Que.
Print_ISBN :
0-7695-0265-2
DOI :
10.1109/IDEAS.1999.787298
