Title: Use of FCA in the Ontology Extraction Step for the Improvement of the Semantic Information Retrieval Peter Butka (Peter.Butka@tuke.sk), TU Ko
1Use 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
2Use 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
3Possible 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