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» Knowledge Discovery in Textual Databases (KDT)
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ISI
2007
Springer
13 years 11 months ago
Mining Higher-Order Association Rules from Distributed Named Entity Databases
The burgeoning amount of textual data in distributed sources combined with the obstacles involved in creating and maintaining central repositories motivates the need for effective ...
Shenzhi Li, Christopher D. Janneck, Aditya P. Bela...
PKDD
1998
Springer
113views Data Mining» more  PKDD 1998»
13 years 9 months ago
Text Mining at the Term Level
Knowledge Discovery in Databases (KDD) focuses on the computerized exploration of large amounts of data and on the discovery of interesting patterns within them. While most work on...
Ronen Feldman, Moshe Fresko, Yakkov Kinar, Yehuda ...
KDD
2007
ACM
154views Data Mining» more  KDD 2007»
14 years 5 months ago
Canonicalization of database records using adaptive similarity measures
It is becoming increasingly common to construct databases from information automatically culled from many heterogeneous sources. For example, a research publication database can b...
Aron Culotta, Michael L. Wick, Robert Hall, Matthe...
DGO
2007
192views Education» more  DGO 2007»
13 years 6 months ago
D-HOTM: distributed higher order text mining
We present D-HOTM, a framework for Distributed Higher Order Text Mining based on named entities extracted from textual data that are stored in distributed relational databases. Unl...
William M. Pottenger