Person: Heikki Mannila

DBLP: Mannila:Heikki

Facilitated 1 volumes:

Ed

Contributed to:

2010

2009

2008

2007

2007

2006

2005

2004

2004

2003

2002

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1991

Wrote 48 papers:

KDD-2010-LappasTGM #network #social

Finding effectors in social networks (TL, ET, DG, HM), pp. 1059–1068.

KDD-2009-HanhijarviOVPTM #data mining #mining

Tell me something I don’t know: randomization strategies for iterative data mining (SH, MO, NV, KP, NT, HM), pp. 379–388.

KDD-2009-Mannila #data mining #mining

Randomization methods in data mining (HM), pp. 5–6.

KDD-2008-GarrigaJM #matrix

Banded structure in binary matrices (GCG, EJ, HM), pp. 292–300.

KDD-2007-HeikinheimoSHMM #set

Finding low-entropy sets and trees from binary data (HH, JKS, EH, HM, TM), pp. 350–359.

KDD-2007-MannilaT

Nestedness and segmented nestedness (HM, ET), pp. 480–489.

SIGMOD-2007-DasguptaDM #approach #database #random

A random walk approach to sampling hidden databases (AD, GD, HM), pp. 629–640.

KDD-2006-GionisMMT #data mining #mining

Assessing data mining results via swap randomization (AG, HM, TM, PT), pp. 167–176.

KDD-2006-GionisMPU #algorithm #order

Algorithms for discovering bucket orders from data (AG, HM, KP, AU), pp. 561–566.

KDD-2005-UkkonenFM #partial order

Finding partial orders from unordered 0-1 data (AU, MF, HM), pp. 285–293.

KDD-2004-AfratiGM #approximate #set

Approximating a collection of frequent sets (FNA, AG, HM), pp. 12–19.

KDD-2004-SeppanenM

Dense itemsets (JKS, HM), pp. 683–688.

VLDB-2004-GeertsMT #ranking #relational

Relational link-based ranking (FG, HM, ET), pp. 552–563.

KDD-2003-GionisKM #order

Fragments of order (AG, TK, HM), pp. 129–136.

ICALP-2002-Mannila #data mining #mining #problem

Local and Global Methods in Data Mining: Basic Techniques and Open Problems (HM), pp. 57–68.

KDD-2002-BinghamMS #topic

Topics in 0--1 data (EB, HM, JKS), pp. 450–455.

KDD-2001-BinghamM #image #random #reduction

Random projection in dimensionality reduction: applications to image and text data (EB, HM), pp. 245–250.

KDD-2001-CadezSM #modelling #predict #probability #profiling #transaction #visualisation

Probabilistic modeling of transaction data with applications to profiling, visualization, and prediction (IVC, PS, HM), pp. 37–46.

KDD-2001-MannilaS #sequence

Finding simple intensity descriptions from event sequence data (HM, MS), pp. 341–346.

KDD-2000-MannilaM #partial order

Global partial orders from sequential data (HM, CM), pp. 161–168.

KDD-1999-MannilaPS #predict #using

Prediction with Local Patterns using Cross-Entropy (HM, DP, PS), pp. 357–361.

KDD-1998-DasLMRS

Rule Discovery from Time Series (GD, KIL, HM, GR, PS), pp. 16–22.

KDD-1998-DasMR #similarity

Similarity of Attributes by External Probes (GD, HM, PR), pp. 23–29.

ILPS-1997-Mannila #data mining #database #induction #mining

Inductive Databases and Condensed Representations for Data Mining (HM), pp. 21–30.

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.

ICML-1996-Mannila #data mining #machine learning #mining

Data Mining and Machine Learning (HM), p. 555.

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.

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.

PODS-1994-EiterGM #datalog

Adding Disjunction to Datalog (TE, GG, HM), pp. 267–278.

PODS-1994-KivinenM #information management #power of

The Power of Sampling in Knowledge Discovery (JK, HM), pp. 77–85.

SIGIR-1993-KilpelainenM #retrieval

Retrieval from Hierarchical Texts by Partial Patterns (PK, HM), pp. 214–222.

PODS-1989-MannilaR #algorithm #normalisation #testing

Practical Algorithms for Finding Prime Attributes and Testing Normal Forms (HM, KJR), pp. 128–133.

SLP-1987-MannilaU87 #analysis #prolog #source code

Flow Analysis of Prolog Programs (HM, EU), pp. 205–214.

VLDB-1987-MannilaR #dependence

Dependency Inference (HM, KJR), pp. 155–158.

ICALP-1986-MannilaU #backtracking #problem #set

The Set Union Problem with Backtracking (HM, EU), pp. 236–243.

ICLP-1986-MannilaU86 #complexity #on the #sequence #unification

On the Complexity of Unification Sequences (HM, EU), pp. 122–133.

PODS-1986-MannilaR #query #relational #testing

Test Data for Relational Queries (HM, KJR), pp. 217–223.

SLP-1986-MannilaU86 #implementation #prolog #representation

Timestamped Term Representation for Implementing Prolog (HM, EU), pp. 159–165.

PODS-1985-MannilaR #database #design

Small Armstrong Relations for Database Design (HM, KJR), pp. 245–250.

ICALP-1984-Mannila #algorithm #metric #sorting

Measures of Presortedness and Optimal Sorting Algorithms (HM), pp. 324–336.

POPL-1983-BackMR #algorithm #graph #performance

Derivation of Efficient DAG Marking Algorithms (RJB, HM, KJR), pp. 20–27.

ICALP-1982-BackM #composition #locality

Locality in Modular Systems (RJB, HM), pp. 1–13.

CAAP-1991-KilpelainenM #problem

The Tree Inclusion Problem (PK, HM), pp. 202–214.