The MIDAS data-mining project at Stanford

Author

Ullman, Jeffrey D.

Author_Institution

Dept. of Comput. Sci., Stanford Univ., CA, USA

fYear

1999

fDate

36373

Firstpage

460

Lastpage

464

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Database Engineering and Applications, 1999. IDEAS '99. International Symposium Proceedings

Conference_Location

Montreal, Que.

Print_ISBN

0-7695-0265-2

Type

conf

DOI

10.1109/IDEAS.1999.787298

Filename

787298