{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:29:54Z","timestamp":1777703394256,"version":"3.51.4"},"reference-count":33,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2015,10,23]],"date-time":"2015-10-23T00:00:00Z","timestamp":1445558400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2015,10,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    This paper aims to incorporate a knowledge discovery technique into the Proximity-based Logic Programming paradigm in order to generate background knowledge (conceptual hierarchies) in a semi-automatic way which may lead to an efficient and desirable abstraction process among the symbols (representing concepts) from a first-order language and to the discovery of generalized relationship among them i.e. a logic-based framework with the capability of abstraction. This method makes use of\u00a0the concept of\n                    <jats:italic>\u03bb<\/jats:italic>\n                    -block characterizing the notion of equivalence when working with proximity relations. When the universe of discourse is composed of concepts which are related by proximity, the sets of\n                    <jats:italic>\u03bb<\/jats:italic>\n                    -blocks extracted from that proximity relation can be seen as hierarchical sets of concepts grouped by abstraction level. Then, each group (forming a\n                    <jats:italic>\u03bb<\/jats:italic>\n                    -block) can be labeled, with user help, by means of a more general descriptor in order to simulate a generalization process based on proximity. Thanks to this process, the system can learn concepts that were unknown initially and reply to queries that it was not able to answer. The novelty of this work is that it is the first time a method, with analogous features to the one aforementioned, is implemented inside a fuzzy logic programming framework. Certainly, in order to check the feasibility of the method, we have developed a software tool which have been integrated into the Bousi~Prolog system. Finally, this work presents a method to get a set of recommended abstract descriptors by using WordNet. This allows to improve the original generalization mechanism, helping the user in the task of selecting a convenient abstraction. Also, the overall method can be seen as a technique that facilitates the tuning of term ontologies.\n                  <\/jats:p>","DOI":"10.3233\/ifs-151645","type":"journal-article","created":{"date-parts":[[2015,11,3]],"date-time":"2015-11-03T11:21:21Z","timestamp":1446549681000},"page":"1671-1683","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Incorporation of abstraction capability in\u00a0a\u00a0logic-based framework by using proximity relations"],"prefix":"10.1177","volume":"29","author":[{"given":"Clemente","family":"Rubio-Manzano","sequence":"first","affiliation":[{"name":"Department of Information Systems, University of the B\u00edo-B\u00edo, Concepci\u00f3n, Chile"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pascual","family":"Juli\u00e1n-Iranzo","sequence":"additional","affiliation":[{"name":"Department of Information Technologies and Systems, University of Castilla-La Mancha, Ciudad Real, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2015,10,23]]},"reference":[{"key":"e_1_3_1_2_2","article-title":"Discovery of Abstract Knowledge from Non-Atomic Attribute Values in Fuzzy Relational Databases","author":"Angryk RA","year":"2005","unstructured":"AngrykRAPetryFE2005Discovery of Abstract Knowledge from Non-Atomic Attribute Values in Fuzzy Relational DatabasesModern Information Processing: From Theory to Applications","journal-title":"Modern Information Processing: From Theory to Applications"},{"key":"e_1_3_1_3_2","doi-asserted-by":"crossref","first-page":"2333","DOI":"10.1016\/j.fss.2006.03.018","article-title":"Restricted Equivalence Functions","volume":"157","author":"Bustice H","year":"2006","unstructured":"BusticeHBarrenecheaEPagolaM2006Restricted Equivalence FunctionsFuzzy Sets and Systems15723332346","journal-title":"Fuzzy Sets and Systems"},{"key":"e_1_3_1_4_2","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1016\/j.fss.2006.09.012","article-title":"Image thresholding using restricted equivalence functions and maximizing the mesaures of similarity","volume":"158","author":"Bustice H","year":"2007","unstructured":"BusticeHBarrenecheaEPagolaM2007Image thresholding using restricted equivalence functions and maximizing the mesaures of similarityFuzzy Sets and Systems158496516","journal-title":"Fuzzy Sets and Systems"},{"key":"e_1_3_1_5_2","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1016\/j.patrec.2007.11.007","article-title":"Relation between restricted dissimilarity functions, restricted equivalence functions and normal EN-functions: Image thresholding invariant","volume":"29","author":"Bustice H","year":"2008","unstructured":"BusticeHBarrenecheaEPagolaM2008Relation between restricted dissimilarity functions, restricted equivalence functions and normal EN-functions: Image thresholding invariantPattern Recognition Letters29525536","journal-title":"Pattern Recognition Letters"},{"key":"e_1_3_1_6_2","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1007\/3-540-48774-3_56","article-title":"Data On, Summaries Based on Gradual Rules","volume":"1625","author":"Bosc P","year":"1999","unstructured":"BoscPPivertOUghettoL1999Data On, Summaries Based on Gradual RulesLecture Notes in Computer Science Volume1625512521","journal-title":"Lecture Notes in Computer Science Volume"},{"key":"e_1_3_1_7_2","doi-asserted-by":"crossref","unstructured":"BronCKerboshJ1973Algorithm 457: Finding All Cliques of an Undirected GraphCommunications of ACM169ACM Press","DOI":"10.1145\/362342.362367"},{"key":"e_1_3_1_8_2","first-page":"26","article-title":"Attribute-Oriented Induction in Relational Databases","author":"Cai Y","year":"1989","unstructured":"CaiYCerconeNHanJ1989Attribute-Oriented Induction in Relational DatabasesProc IJCAI-892636","journal-title":"Proc IJCAI-89"},{"issue":"3","key":"e_1_3_1_9_2","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/S0020-0255(99)00104-8","article-title":"Data Summarization in Relational Databases Through Fuzzy Dependencies","volume":"121","author":"Cubero JC","year":"1999","unstructured":"CuberoJCMedinaJMPonsOVilaMA1999Data Summarization in Relational Databases Through Fuzzy DependenciesInformation Sciences1213-4233270","journal-title":"Information Sciences"},{"key":"e_1_3_1_10_2","first-page":"1035","article-title":"Fuzzy sets in data summaries - Outline of a new approach. 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