Spatial Indexing for Scalability in FCA | Zendy

Ben Martin | Zendy; Peter Eklund | Zendy

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Spatial Indexing for Scalability in FCA

Author(s) -

Ben Martin,

Peter Eklund

Publication year - 2006

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-32203-5

DOI - 10.1007/11671404_14

Subject(s) - search engine indexing , computer science , scalability , formal concept analysis , hash function , benchmarking , listing (finance) , data mining , information retrieval , matching (statistics) , theoretical computer science , database , algorithm , programming language , mathematics , marketing , economics , business , statistics , finance

The paper provides evidence that spatial indexing structures offer faster resolution of Formal Concept Analysis queries than B-Tree/Hash methods. We show that many Formal Concept Analysis operations, computing the contingent and extent sizes as well as listing the matching objects, enjoy improved performance with the use of spatial indexing structures such as the RD-Tree. Speed improvements can vary up to eighty times faster depending on the data and query. The motivation for our study is the application of Formal Concept Analysis to Semantic File Systems. In such applications millions of formal objects must be dealt with. It has been found that spatial indexing also provides an effective indexing technique for more general purpose applications requiring scalability in Formal Concept Analysis systems. The coverage and benchmarking are presented with general applications in mind.

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