BibSLEIGH corpus
BibSLEIGH tags
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Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
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Travelled to:
1 × Australia
1 × Canada
1 × India
1 × Italy
7 × USA
Collaborated with:
H.Mannila A.I.Verkamo L.Langohr O.Gross A.Doucet P.Sevon V.Ollikainen L.Dehaspe R.D.King F.Zhou A.Hartikainen A.Hinkka D.Gunopulos R.Khardon M.Holsheimer M.L.Kersten R.Agrawal R.Srikant M.Klemettinen P.Ronkainen
Talks about:
associ (5) rule (5) discov (4) frequent (3) mine (3) databas (2) episod (2) tree (2) larg (2) find (2)

Person: Hannu Toivonen

DBLP DBLP: Toivonen:Hannu

Contributed to:

SIGIR 20142014
SAC 20122012
KDD 20112011
KDD 20012001
KDD 19981998
PODS 19971997
KDD 19961996
KDD 19961996
VLDB 19961996
KDD 19951995
CIKM 19941994
KDD 19941994

Wrote 14 papers:

SIGIR-2014-GrossDT #documentation #summary #word
Document summarization based on word associations (OG, AD, HT), pp. 1023–1026.
SAC-2012-LangohrT #mining
A model for mining relevant and non-redundant information (LL, HT), pp. 132–137.
KDD-2011-ToivonenZHH #graph
Compression of weighted graphs (HT, FZ, AH, AH), pp. 965–973.
KDD-2001-SevonTO #named
TreeDT: gene mapping by tree disequilibrium test (PS, HT, VO), pp. 365–370.
Finding Frequent Substructures in Chemical Compounds (LD, HT, RDK), pp. 30–36.
PODS-1997-GunopulosKMT #data mining #machine learning #mining
Data mining, Hypergraph Transversals, and Machine Learning (DG, RK, HM, HT), pp. 209–216.
AKDDM-1996-AgrawalMSTV #performance
Fast Discovery of Association Rules (RA, HM, RS, HT, AIV), pp. 307–328.
KDD-1996-MannilaT #using
Discovering Generalized Episodes Using Minimal Occurrences (HM, HT), pp. 146–151.
KDD-1996-MannilaT96a #multi #set
Multiple Uses of Frequent Sets and Condensed Representations (HM, HT), pp. 189–194.
VLDB-1996-Toivonen #database #scalability
Sampling Large Databases for Association Rules (HT), pp. 134–145.
KDD-1995-HolsheimerKMT #data mining #database #mining
A Perspective on Databases and Data Mining (MH, MLK, HM, HT), pp. 150–155.
KDD-1995-MannilaTV #sequence
Discovering Frequent Episodes in Sequences (HM, HT, AIV), pp. 210–215.
CIKM-1994-KlemettinenMRTV #scalability #set
Finding Interesting Rules from Large Sets of Discovered Association Rules (MK, HM, PR, HT, AIV), pp. 401–407.
KDD-1994-MannilaTV #algorithm #performance
Efficient Algorithms for Discovering Association Rules (HM, HT, AIV), pp. 181–192.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.