Stem interesting$ (all stems)

15 papers:

SANER-2015-LeL #metric #mining #rule-based #specification

Beyond support and confidence: Exploring interestingness measures for rule-based specification mining (TDBL, DL), pp. 331–340.

SAC-2010-HeraviZ #case study #classification #metric

A study on interestingness measures for associative classifiers (MJH, ORZ), pp. 1039–1046.

KDIR-2009-Exman #composition #named #paradigm

Interestingness — A Unifying Paradigm — Bipolar Function Composition (IE), pp. 196–201.

MLDM-2007-HebertC #metric

A Unified View of Objective Interestingness Measures (CH, BC), pp. 533–547.

ICEIS-AIDSS-2006-HuynhGB #clustering #metric

Discovering the Stable Clusters between Interestingness Measures (HXH, FG, HB), pp. 196–201.

KDD-2006-LiuZBX #analysis #using

Rule interestingness analysis using OLAP operations (BL, KZ, JB, WX), pp. 297–306.

ICEIS-v2-2005-HuynhGB #clustering #metric

Clustering Interestingness Measures with Positive Correaltion (HXH, FG, HB), pp. 248–253.

SAC-2005-NatarajanS #approach #data-driven

A relatedness-based data-driven approach to determination of interestingness of association rules (RN, BS), pp. 551–552.

KDD-2004-JaroszewiczS #network #using

Interestingness of frequent itemsets using Bayesian networks as background knowledge (SJ, DAS), pp. 178–186.

CIKM-2002-HuangCA #comparison #learning #web

Comparison of interestingness functions for learning web usage patterns (XH, NC, AA), pp. 617–620.

KDD-2002-TanKS

Selecting the right interestingness measure for association patterns (PNT, VK, JS), pp. 32–41.

KDD-1999-Sahar #what

Interestingness via What is Not Interesting (SS), pp. 332–336.

KDD-1998-WangTL

Interestingness-Based Interval Merger for Numeric Association Rules (KW, SHWT, BL), pp. 121–128.

KDD-1996-KamberS

Evaluating the Interestingness of Characteristic Rules (MK, RS), pp. 263–266.

KDD-1995-SilberschatzT #information management #metric #on the

On Subjective Measures of Interestingness in Knowledge Discovery (AS, AT), pp. 275–281.