Formal Concept Analysis

  title={Formal Concept Analysis},
  author={Florent Domenach and D. Ignatov and Jonas Poelmans},
  booktitle={Lecture Notes in Computer Science},
This talk will review the emerging research in Terrorism Informatics based on a web mining perspective. Recent progress in the internationally renowned Dark Web project will be reviewed, including: deep/dark web spidering (web sites, forums, Youtube, virtual worlds), web metrics analysis, dark network analysis, web-based authorship analysis, and sentiment and affect analysis for terrorism tracking. In collaboration with selected international terrorism research centers and intelligence agencies… 
3 Citations

Concept Membership Modeling Using a Choquet Integral

A valuable property of the proposed approach is that it is able to both capture properties shared by most of the user-selected representative data points as well as specific properties possessed by only one specific representative data point.

Rough Sets and FCA - Scalability Challenges

This talk attempts to categorize some ideas of how to scale RS and FCA methods with respect to a number of objects and attributes, as well as types and cardinalities of attribute values.

Analytic Methods for Spatio-Temporal Data in a Nature-Inspired Data Model

The main objectives of this research are to propose a model to achieve better knowledge representation, provide the capability to expand queries through additional analytical attributes and reduce redundancy, and thereby obtain better integrity and consistency in spatio-temporal databases.



The Anatomy of a Large-Scale Hypertextual Web Search Engine

Text Mining Scientific Papers: A Survey on FCA-Based Information Retrieval Research

The core contributions of this paper are the innovative application of FCA to the text mining of scientific papers and the survey of the FCA-based IR research.

Analysis of Social Communities with Iceberg and Stability-Based Concept Lattices

This work focuses on the ability of concept lattices to discover and represent special groups of individuals, called social communities, and relies on concept stability and support measures to reduce the size of large concept lattice.

Formal Concept Analysis in Knowledge Discovery: A Survey

This paper analyzes the literature on Formal Concept Analysis using FCA, and uses the visualization capabilities of FCA to explore the literature, to discover and conceptually represent the main research topics in the FCA community.

Formal Concept Analysis for Knowledge Discovery and Data Mining: The New Challenges

The existing ARM methods are discussed, a set of guidelines for the design of novel ones are provided, and some open algorithmic issues on the FCA side are list and two on-line methods computing the minimal generators of a closure system are proposed.

Computing iceberg concept lattices with T

Machine Learning and Formal Concept Analysis

This work shows how the means of FCA allows one to realize learning in this model with various data representation, from standard object-attribute one to that with labeled graphs, and considers applications of the concept-based learning, including Structure-Activity Relationship problem (in predictive toxicology and spam filtering.

Concept data analysis - theory and applications

Mining the Content of the ACM Digital Library and MiningWeb Retrieval Results with CREDO: Theoretical Foundations and Applications.

The influence of author self-citations on bibliometric macro indicators

The analysis of citation based indicators for 15 fields in the sciences, social sciences and humanities substantiates that at this level of aggregation there is no need for any revision of national indicators and the underlying journal citation measures in the context of excluding self-citations.

Citation Analysis using Formal Concept Analysis: A case study in Software Engineering

  • T. TilleyPeter W. Eklund
  • Computer Science
    18th International Workshop on Database and Expert Systems Applications (DEXA 2007)
  • 2007
In this paper formal concept analysis (FCA) is used as a means to analyse afield of research using published academic papers as its input, and reveals useful insights about the nature of the subject matter.