{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T20:34:48Z","timestamp":1674506088215},"reference-count":12,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Found. Comput. Sci."],"published-print":{"date-parts":[[2008,4]]},"abstract":"<jats:p> The paper presents results on factorization by similarity of fuzzy concept lattices with hedges. A fuzzy concept lattice is a hierarchically ordered collection of clusters extracted from tabular data. The basic idea of factorization by similarity is to have, instead of a possibly large original fuzzy concept lattice, its factor lattice. The factor lattice contains less clusters than the original concept lattice but, at the same time, represents a reasonable approximation of the original concept lattice and provides us with a granular view on the original concept lattice. The factor lattice results by factorization of the original fuzzy concept lattice by a similarity relation. The similarity relation is specified by a user by means of a single parameter, called a similarity threshold. Smaller similarity thresholds lead to smaller factor lattices, i.e. to more comprehensible but less accurate approximations of the original concept lattice. Therefore, factorization by similarity provides a trade-off between comprehensibility and precision. <\/jats:p><jats:p> We first describe the notion of factorization. Second, we present a way to compute the factor lattice directly from input data, i.e. without the need to compute the possibly large original concept lattice. Third, we provide an illustrative example to demonstrate our method. <\/jats:p>","DOI":"10.1142\/s012905410800567x","type":"journal-article","created":{"date-parts":[[2008,4,10]],"date-time":"2008-04-10T11:30:22Z","timestamp":1207827022000},"page":"255-269","source":"Crossref","is-referenced-by-count":10,"title":["FAST FACTORIZATION BY SIMILARITY OF FUZZY CONCEPT LATTICES WITH HEDGES"],"prefix":"10.1142","volume":"19","author":[{"given":"RADIM","family":"B\u011aLOHL\u00c1VEK","sequence":"first","affiliation":[{"name":"Dept. Systems Science &amp; Industrial Eng., Binghamton University \u2013 SUNY, Binghamton, NY, 13902, USA"},{"name":"Department of Computer Science, Palacky University, Olomouc, Tomkova 40, CZ-779 00 Olomouc, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"JAN","family":"OUTRATA","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Palacky University, Olomouc, Tomkova 40, CZ-779 00 Olomouc, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"VILEM","family":"VYCHODIL","sequence":"additional","affiliation":[{"name":"Dept. Systems Science &amp; Industrial Eng., Binghamton University \u2013 SUNY, Binghamton, NY, 13902, USA"},{"name":"Department of Computer Science, Palacky University, Olomouc, Tomkova 40, CZ-779 00 Olomouc, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,20]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1002\/malq.19990450408"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1093\/logcom\/10.6.823"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-0633-1"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1016\/j.apal.2003.01.001"},{"key":"rf12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-1825-3_7"},{"key":"rf13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-59830-2"},{"key":"rf14","first-page":"325","volume":"18","author":"Goguen J. 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