Frequent item set mining
Frequent item set mining is one of the best known and most popular data mining methods.
Originally developed for market basket analysis, it is used nowadays for almost any task that …
Originally developed for market basket analysis, it is used nowadays for almost any task that …
Formal concept analysis in knowledge processing: A survey on models and techniques
This is the first part of a large survey paper in which we analyze recent literature on Formal
Concept Analysis (FCA) and some closely related disciplines using FCA. We collected 1072 …
Concept Analysis (FCA) and some closely related disciplines using FCA. We collected 1072 …
Formal concept analysis in knowledge discovery: a survey
In this paper, we analyze the literature on Formal Concept Analysis (FCA) using FCA. We
collected 702 papers published between 2003-2009 mentioning Formal Concept Analysis in …
collected 702 papers published between 2003-2009 mentioning Formal Concept Analysis in …
Constraint programming for mining n-ary patterns
The aim of this paper is to model and mine patterns combining several local patterns (n-ary
patterns). First, the user expresses his/her query under constraints involving n-ary patterns …
patterns). First, the user expresses his/her query under constraints involving n-ary patterns …
Exceptional contextual subgraph mining
Many relational data result from the aggregation of several individual behaviors described
by some characteristics. For instance, a bike-sharing system may be modeled as a graph …
by some characteristics. For instance, a bike-sharing system may be modeled as a graph …
Biclustering meets triadic concept analysis
Biclustering numerical data became a popular data-mining task at the beginning of 2000's,
especially for gene expression data analysis and recommender systems. A bicluster reflects …
especially for gene expression data analysis and recommender systems. A bicluster reflects …
Concept-based biclustering for internet advertisement
The problem of detecting terms that can be interesting to the advertiser is considered. If a
company has already bought some advertising terms which describe certain services, it is …
company has already bought some advertising terms which describe certain services, it is …
Mining maximal quasi‐bicliques: Novel algorithm and applications in the stock market and protein networks
Several real‐world applications require mining of bicliques, as they represent correlated
pairs of data clusters. However, the mining quality is adversely affected by missing and noisy …
pairs of data clusters. However, the mining quality is adversely affected by missing and noisy …
Can triconcepts become triclusters?
Two novel approaches to triclustering of three-way binary data are proposed. Tricluster is
defined as a dense subset of a ternary relation Y defined on sets of objects, attributes, and …
defined as a dense subset of a ternary relation Y defined on sets of objects, attributes, and …
Gaining insight in social networks with biclustering and triclustering
We combine bi-and triclustering to analyse data collected from the Russian online social
network Vkontakte. Using biclustering we extract groups of users with similar interests and …
network Vkontakte. Using biclustering we extract groups of users with similar interests and …