Use%20of%20FCA%20in%20the%20Ontology%20Extraction%20Step%20for%20the%20Improvement%20of%20the%20Semantic%20Information%20Retrieval%20Peter%20Butka%20([e-mail]),%20TU%20Ko

1
Use of FCA in the Ontology Extraction Step for
the Improvement of the Semantic Information
RetrievalPeter Butka (Peter.Butka_at_tuke.sk), TU
Košice, Slovakia

• Semantic Web Environment and Retrieval Tasks
• Information retrieval improvement of unknown set
  of text documents
• Preprocessing of documents set
• Building of the ontology
• Creating of concept hierarchy
• Finding of relations between concepts
• Extraction of instances (ontology population)
• Using of created ontology and instances for the
  improvement of IR

2
Use of FCA and labeling of concepts

• Formal Concept Analysis
• Explorative method for data analysis
• Concept lattice
• Concept is cluster of similar objects
  (similarity is based on presence of same
  attributes)
• Concepts are hierarchically organized (specific
  vs. general)
• Use of FCA on texts
• Output one-sided fuzzy concept lattice
• Clustering via concepts (agglomerative)
• Interpretation
• Use of LabelSOM method for improving of
  interpretability of concepts (clusters)

Concept (467) IntSet 467(467 2) 6
59 Labels (467) indian 0.0849, provinc
0.125887, negoti 0.127356, nehru 0.14293, kashmir
0.149645, india 0.169807, pakistan 0.200657
3
Possible use of reduction approach to ontology
creation step

• FCA and texts
• interpretability problems
• time-consuming
• Solution problem reduction gt e.g. use of
  clustering algorithms
• Pre-clustering of document set (e.g. Hierarchical
  SOM)
• Creation of ontology parts from smaller sets
  (FCA)
• Merging of small models to complete ontology