THIS PAPER PRESENTS A PRELIMINARY STUDY OF THE APPLICATION OF FORMAL CONCEPT ANALYSIS TO AUTOMATIC DRIVER IDENTIFICATION. SPECIFICALLY, A METHODOLOGY BASED ON ATTRIBUTE IMPLICATIONS HAS BEEN CONSIDERED AND ITS MAIN FEATURES HAVE BEEN STUDIED. FROM A PARTICULAR DATASET, THE PROPOSED METHODOLOGY FOCUSES ON DRIVER RECOGNITION BY ANALYZING THE VALUES OF A SUBSET OF VARIABLES RELATED TO DRIVING STYLE.

IN THIS WORK A FUZZY LINGUISTIC PROLOG LANGUAGE IS PRESENTED AND ITS DESIGN, IMPLEMENTATION AND APPLICATIONS ARE DETAILED. A FUZZY LINGUISTIC PROLOG IS A FUZZY PROLOG WHICH ALLOWS TO WORK WITH BOTH FUZZY LINGUISTIC AND LINGUISTIC TOOLS IN ORDER TO GEAR THE PROLOG SYSTEMS TOWARDS THE COMPUTING WITH WORDS PARADIGM IN WHICH THE LINGUISTIC RESOURCES CAN BE VERY USEFUL.

PURPOSE:THIS PAPER AIMS TO DESCRIBE THE PROCESS USED TO CREATE AN EMOTION LEXICON ENRICHED WITH THE EMOTIONAL INTENSITY OF WORDS AND FOCUSES ON IMPROVING THE EMOTION ANALYSIS PROCESS IN TEXTS. DESIGN/METHODOLOGY/APPROACH ? THE PROCESS INCLUDES SETTING, PREPARATION AND LABELLING STAGES. IN THE FIRST STAGE, A LEXICON IS SELECTED. IT MUST INCLUDE A TRANSLATION TO THE TARGET LANGUAGE AND LABELLING ACCORDING TO PLUTCHIK?S EIGHT EMOTIONS. THE SECOND STAGE STARTS WITH THE VALIDATION OF THE TRANSLATIONS. THEN, IT IS EXPANDED WITH THE SYNONYMS OF THE EMOTION SYNSETS OF EACH WORD. IN THE LABELLING STAGE, THE SIMILARITY OF WORDS IS CALCULATED AND DISPLAYED USING WORDNET SIMILARITY. FINDINGS ? THE AUTHORS? APPROACH SHOWS BETTER PERFORMANCE TO IDENTIFICATION OF THE PREDOMINANT EMOTION FOR THE SELECTED CORPUS. THE MOST RELEVANT IS THE IMPROVEMENT OBTAINED IN THE RESULTS OF THE EMOTION ANALYSIS IN A HYBRID APPROACH COMPARED TO THE RESULTS OBTAINED IN A PURIST APPROACH. RESEARCH LIMITATIONS/IMPLICATIONS ? THE PROPOSED LEXICON CAN STILL BE ENRICHED BY INCORPORATING ELEMENTS SUCH AS EMOJIS, IDIOMS AND COLLOQUIAL EXPRESSIONS. PRACTICAL IMPLICATIONS ? THIS WORK IS PART OF A RESEARCH PROJECT THAT AIDS IN SOLVING PROBLEMS IN A DIGITAL SOCIETY, SUCH AS DETECTING CYBERBULLYING, ABUSIVE LANGUAGE AND GENDER VIOLENCE IN TEXTS OR EXERCISING PARENTAL CONTROL. DETECTION OF DEPRESSIVE STATES IN YOUNG PEOPLE AND CHILDREN IS ADDED. ORIGINALITY/VALUE ? THIS SEMI-AUTOMATIC PROCESS CAN BE APPLIED TO ANY LANGUAGE TO GENERATE AN EMOTION LEXICON. THIS RESOURCE WILL BE AVAILABLE IN A SOFTWARE TOOL THAT IMPLEMENTS A CROWDSOURCING STRATEGY ALLOWING THE INTENSITY TO BE RE-LABELLED AND NEW WORDS TO BE AUTOMATICALLY INCORPORATED INTO THE LEXICON.

IN THIS PAPER, WE PRESENT A NEW INTEGRATION APPROACH FOR MANAGING INFORMATION TECHNOLOGY VARIABLES WITHIN ENTERPRISE ARCHITECTURE IN AN INTEGRATED WAY. ADDITIONIALLY, A NOVEL METHOD BASED ON FUZZY LOGIC FOR CAUSE-EFFECT VARIABLE ANALYSIS IS PROPOSED AS A USEFUL SUPPORT DECISION-MAKING TOOL FOR COMPANIES IN ORDER TO KNOW THE MAIN ACTIONS THEY MUST PERFORM FOR INCREASING THEIR BENEFITS. THIS IS EMPLOYED TO ASSESS THE INTEGRATION MANAGEMENT SYSTEM IN ENTERPRISES, BASED ON ENTERPRISE ARCHITECTURE AND INFORMATION TECHNOLOGY. WE SHOW AS FUZZY LOGIC PLAYS AN IMPORTANT ROLE IN THIS AREA DUE TO THESE VARIABLES CAN BE AFFECTED FOR MULTIFACTORIAL ELEMENTS IMPREGNATED WITH UNCERTAINTY. THE KNOWLEDGE GIVEN BY THE EXPERTS IS TRANSLATED INTO DEPENDENCE RULES, WHICH HAVE ALSO BEEN ANALYZED FROM A FUZZY POINT OF VIEW USING A COMBINATION OF TWO FUZZY TECHNIQUES, NAMELY, FUZZY RELATION EQUATION THEORY AND FUZZY GRAPH. FIRSTLY, FUZZY DEPENDENCE RULES ARE COMPUTED FROM FUZZY RELATION EQUATIONS AND, SECONDLY, AN ANALYSIS BASED ON INCIDENCE SUBGRAPH IS PERFORMED. THE RESULT IS A STRATEGIC PLAN AUTOMATICALLY GENERATED FROM THE DATA CAPTURED OF EACH ENTERPRISE IN WHICH THE MOST IMPORT VARIABLES TO BE IMPROVED ARE DETAILED.

IN THIS WORK, A PROXIMITY-BASED GENERIC METHOD FOR DISCOVERY OF GENERALIZED KNOWLEDGE IS PRESENTED AND IMPLEMENTED IN THE FRAMEWORK OF A FUZZY LOGIC PROGRAMMING LANGUAGE WITH A WEAK UNIFICATION PROCEDURE THAT USES PROXIMITY RELATIONS TO MODEL UNCERTAINTY. THIS METHOD MAKES USE OF THE CONCEPT OF ?-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 ?-BLOCKS EXTRACTED FROM THAT PROXIMITY RELATION CAN BE SEEN AS HIERARCHICAL SETS OF CONCEPTS GROUPED BY ABSTRACTION LEVEL. THEN, EACH GROUP (FORMING A ?-BLOCK) CAN BE LABELED, WITH USER HELP, BY WAY 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 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, HAS BEEN IMPLEMENTED INSIDE A FUZZY LOGIC PROGRAMMING FRAMEWORK. IN ORDER TO CHECK THE FEASIBILITY OF THE METHOD WE HAVE DEVELOPED A SOFTWARE TOOL WHICH HAVE BEEN INTEGRATED INTO THE BOUSI~PROLOG SYSTEM.

SIMILARITY-BASED LOGIC PROGRAMMING REPLACES THE SYNTACTIC UNIFICATION ALGORITHM OF CLASSICAL SLD-RESOLUTION BY A FUZZY ONE, LEADING TO AN OPERATIONAL MECHANISM THAT WE NAME WEAK SLD-RESOLUTION. THIS IS THE OPERATIONAL SEMANTICS OF A SUBSET OF BOUSI?PROLOG, AN EXTENSION OF PROLOG AIMING AT MAKING THE QUERY ANSWERING PROCESS MORE FLEXIBLE. IN THIS PAPER, AFTER RECALLING THE MODEL-THEORETIC AND FIXPOINT SEMANTICS FOR A PURE SUBSET OF THIS LANGUAGE, WE DETAIL THE OPERATIONAL SEMANTICS OF BOUSI?PROLOG AND WE PROVE, AMONG OTHER RESULTS, ITS SOUNDNESS AND COMPLETENESS. SIGNIFICANTLY, THROUGHOUT THIS WORK WE ALSO CLARIFY SOME OF THE DIFFERENCES BETWEEN OUR FRAMEWORK AND OTHER RELATED PROPOSALS.

17TH INTERNATIONAL CONFERENCE COMPUTATIONAL AND MATHEMATICAL METHODS IN SCIENCE AND ENGINEERING. COSTA BALLENA, ROTA (CÁDIZ), ESPAÑA

BOUSI~PROLOG IS A FUZZY LOGIC PROGRAMMING LANGUAGE WITH AN OPERATIONAL SEMANTICS WHICH IS AN ADAPTATION OF THE SLD RESOLUTION PRINCIPLE, WHERE CLASSICAL UNIFICATION HAS BEEN REPLACED BY A FUZZY UNIFICATION ALGORITHM BASED ON FUZZY RELATIONS. HENCE, IT IS A PROGRAMMING LANGUAGE WELL SUITED FOR DEALING WITH VAGUENESS AND APPROXIMATE REASONING. IN THIS PAPER WE SUMMARIZE ITS DESIGN AND IMPLEMENTATION.

IN RECENT YEARS, THE USE OF SOCIAL NETWORKS HAS INCREASED EXPONENTIALLY, WHICH HAS LED TO A SIGNIFICANT INCREASE IN CYBERBULLYING. CURRENTLY, IN THE FIELD OF COMPUTER SCIENCE, RESEARCH HAS BEEN MADE ON HOW TO DETECT AGGRESSIVENESS IN TEXTS, WHICH IS A PRELUDE TO DETECTING CYBERBULLYING. IN THIS FIELD, THE MAIN WORK HAS BEEN DONE FOR ENGLISH LANGUAGE TEXTS, MAINLY USING MACHINE LEARNING (ML) APPROACHES, LEXICON APPROACHES TO A LESSER EXTENT, AND VERY FEW WORKS USING HYBRID APPROACHES. IN THESE, LEXICONS AND MACHINE LEARNING ALGORITHMS ARE USED, SUCH AS COUNTING THE NUMBER OF BAD WORDS IN A SENTENCE USING A LEXICON OF BAD WORDS, WHICH SERVES AS AN INPUT FEATURE FOR CLASSIFICATION ALGORITHMS. THIS RESEARCH AIMS AT CONTRIBUTING TOWARDS DETECTING AGGRESSIVENESS IN SPANISH LANGUAGE TEXTS BY CREATING DIFFERENT MODELS THAT COMBINE THE LEXICONS AND ML APPROACH. TWENTY-TWO MODELS THAT COMBINE TECHNIQUES AND ALGORITHMS FROM BOTH APPROACHES ARE PROPOSED, AND FOR THEIR APPLICATION, CERTAIN HYPERPARAMETERS ARE ADJUSTED IN THE TRAINING DATASETS OF THE CORPORA, TO OBTAIN THE BEST RESULTS IN THE TEST DATASETS. THREE SPANISH LANGUAGE CORPORA ARE USED IN THE EVALUATION: CHILEAN, MEXICAN, AND CHILEAN-MEXICAN CORPORA. THE RESULTS INDICATE THAT HYBRID MODELS OBTAIN THE BEST RESULTS IN THE 3 CORPORA, OVER IMPLEMENTED MODELS THAT DO NOT USE LEXICONS. THIS SHOWS THAT BY MIXING APPROACHES, AGGRESSIVENESS DETECTION IMPROVES. FINALLY, A WEB APPLICATION IS DEVELOPED THAT GIVES APPLICABILITY TO EACH MODEL BY CLASSIFYING TWEETS, ALLOWING EVALUATING THE PERFORMANCE OF MODELS WITH EXTERNAL CORPUS AND RECEIVING FEEDBACK ON THE PREDICTION OF EACH ONE FOR FUTURE RESEARCH. IN ADDITION, AN API IS AVAILABLE THAT CAN BE INTEGRATED INTO TECHNOLOGICAL TOOLS FOR PARENTAL CONTROL, ONLINE PLUGINS FOR WRITING ANALYSIS IN SOCIAL NETWORKS, AND EDUCATIONAL TOOLS, AMONG OTHERS.

THIS PAPER WILL STUDY HOW FUZZY RELATION EQUATIONS CAN BE APPLIED TO DETERMINE A SET OF RULES THAT SIMULATE THE INTERRELATIONS AMONG THE DETERMINANT VARIABLES CONSIDERED IN THE STRATEGIC MANAGEMENT MODEL FOCUSED ON THE ENTERPRISE ARCHITECTURE, TO GET A COMPLETE INTEGRATION MANAGEMENT SYSTEM IN THE ENTERPRISE (SMEA-IMSE). THE PROPOSED PROCEDURE WILL BE APPLIED TO THE FIRST STATE OF THIS MODEL ON REAL DATA .

CONTEMPORARY POST-INDUSTRIAL URBAN AREAS FACE OPPOSING TRANSFORMATION TRENDS: ON ONE HAND, ABANDONMENT OR UNDERUTILIZATION, AND ITS REPLACEMENT BY NEW CONSTRUCTIONS AND USES, ON THE OTHER HAND, THE REVALUATION OF THE HISTORICAL FABRIC AND THE IMPLEMENTATION OF INITIATIVES TO REHABILITATE THIS LEGACY AS INDUSTRIAL HERITAGE. THIS STUDY AIMED TO UNDERSTAND THE FACTORS THAT INFLUENCE TRENDS, AND SIMULATE LAND-USE SCENARIOS. A METHODOLOGY BASED ON THREE PHASES IS PROPOSED: DIGITIZATION, EXPLORATORY SPATIAL DATA ANALYSIS AND SIMULATION. USING THE FORMER TEXTILE DISTRICT OF BELLAVISTA IN TOMÉ (CHILE), THIS STUDY CREATED AND USED HISTORICAL LAND-USE MAPS FROM 1970, 1992 AND 2019. MEANWHILE THE MAIN CHANGE OBSERVED FROM 1970 TO 1992 WAS A 59.4% REDUCTION IN HISTORICAL INFORMAL OPEN SPACES. THE MAJOR CHANGE FROM 1992 TO 2019 WAS THE HISTORICAL INFORMAL OPEN SPACE LOSS TREND CONTINUING; 65% OF THE LAND DEDICATED TO THIS USE CHANGED TO NEW USAGES. CONSEQUENTLY, THE INFLUENCE OF TWO MORPHOLOGICAL FACTORS AND THREE URBAN MANAGEMENT INSTRUMENTS ON LAND-USE CHANGES BETWEEN 1992 AND 2019 WAS STUDIED. THE PROJECTION TO 2030 SHOWED A CONTINUED TREND OF EXPANSION OF NEW HOUSING USES OVER HISTORIC URBAN GREEN SPACES AND INDUSTRIAL AREAS ON THE WATERFRONT, ALTHOUGH RESTRAINED BY THE PRESERVATION OF THE CENTRAL AREAS OF HISTORIC HOUSING AND THE TEXTILE FACTORY.

HOPFIELD NEURAL NETWORKS (HNNS) ARE RECURRENT NEURAL NETWORKS USED TO IMPLEMENT ASSOCIATIVE MEMORY. THEY CAN BE APPLIED TO PATTERN RECOGNITION, OPTIMIZATION, OR IMAGE SEGMENTATION. HOWEVER, SOMETIMES IT IS NOT EASY TO PROVIDE THE USERS WITH GOOD EXPLANATIONS ABOUT THE RESULTS OBTAINED WITH THEM DUE TO MAINLY THE LARGE NUMBER OF CHANGES IN THE STATE OF NEURONS (AND THEIR WEIGHTS) PRODUCED DURING A PROBLEM OF MACHINE LEARNING. THERE ARE CURRENTLY LIMITED TECHNIQUES TO VISUALIZE, VERBALIZE, OR ABSTRACT HNNS. THIS PAPER OUTLINES HOW WE CAN CONSTRUCT AUTOMATIC VIDEO-GENERATION SYSTEMS TO EXPLAIN ITS EXECUTION. THIS WORK CONSTITUTES A NOVEL APPROACH TO OBTAIN EXPLAINABLE ARTIFICIAL INTELLIGENCE SYSTEMS IN GENERAL AND HNNS IN PARTICULAR BUILDING ON THE THEORY OF DATA-TO-TEXT SYSTEMS AND SOFTWARE VISUALIZATION APPROACHES. WE PRESENT A COMPLETE METHODOLOGY TO BUILD THESE KINDS OF SYSTEMS. SOFTWARE ARCHITECTURE IS ALSO DESIGNED, IMPLEMENTED, AND TESTED. TECHNICAL DETAILS ABOUT THE IMPLEMENTATION ARE ALSO DETAILED AND EXPLAINED. WE APPLY OUR APPROACH TO CREATING A COMPLETE EXPLAINER VIDEO ABOUT THE EXECUTION OF HNNS ON A SMALL RECOGNITION PROBLEM. FINALLY, SEVERAL ASPECTS OF THE VIDEOS GENERATED ARE EVALUATED (QUALITY, CONTENT, MOTIVATION AND DESIGN/PRESENTATION).

IN RECENT TIMES, THE FIELD OF COMPUTER PROGRAMMING HAS EXPERIENCED A SIGNIFICANT REVOLUTION, THANKS TO ADVANCEMENTS IN MACHINE LEARNING. APPLICATIONS HAVE EMERGED WITH THE CAPABILITY TO GENERATE SOURCE CODE FROM NATURAL LANGUAGE DESCRIPTIONS. THESE TOOLS PRIMARILY UTILIZE LANGUAGE MODELS BASED ON DEEP LEARNING, WHICH HAVE BEEN TRAINED ON A COLLECTION OF PROGRAMS AND PROJECTS HOSTED IN PUBLIC REPOSITORIES. ONE OF THESE TOOLS IS GITHUB COPILOT, AN ARTIFICIAL INTELLIGENCE CAPABLE OF GENERATING SOURCE CODE THAT CAN BE INTEGRATED AS AN EXTENSION INTO DEVELOPMENT ENVIRONMENTS. THE OBJECTIVE OF THIS STUDY IS TO EXPERIMENTALLY EXPLORE, ANALYZE, AND EVALUATE THE SUGGESTIONS MADE BY THE GITHUB COPILOT TOOL IN PROGRAMMING TOPICS RELATED TO THE COMPUTER SCIENCE DEGREE AT THE UNIVERSITY OF BIO-BIO. WE PROPOSE FIVE STEPS: (1) COLLECTING NATURAL LANGUAGE STATEMENTS FOR BOTH GENERAL AND SPECIFIC PROGRAMMING PROBLEMS; (2) UTILIZING GITHUB COPILOT TO GENERATE PROGRAMS; (3) EVALUATING ITS PERFORMANCE; (4) CONDUCTING AN ANALYSIS; AND (5) MEASURING CODE QUALITY. THIS APPROACH ALLOWS US TO GAIN AN INITIAL UNDERSTANDING OF ITS EFFECTIVENESS, EMPHASIZING ITS APPLICATION FOR WELL-ESTABLISHED PROBLEMS AND MONITORING ITS USE FOR PROBLEMS WITH DISTINCT OBJECTIVES.

NOWADAYS, THE USE OF RENEWABLE ENERGY IS A PRIORITY FOR GOVERNMENTS AROUND THE WORLD SINCE IT GIVES RISE TO ENERGY SAVING AND ENVIRONMENTAL SUSTAINABILITY. IN THE CASE OF PHOTOVOLTAIC SYSTEMS, IT IS FUNDAMENTAL, TO KNOW HOW MUCH ENERGY CAN BE GENERATED AND HOW MUCH ENERGY IS NEEDED IN ORDER TO MAINTAIN A SUITABLE BALANCE BETWEEN SUPPLY AND DEMAND. IN THIS PAPER, A FORMAL ANALYSIS OF SOLAR POWER AND WEATHER DATA IS PERFORMED IN ORDER TO STUDY HOW THE ENERGY GENERATED BY SOLAR PANELSDEPENDS ON SUNNY DAYS AND WEATHER CONDITIONS. IN PARTICULAR, A SOFTWARE ARCHITECTURE IS PROPOSED WHICH IS FORMED BY THREE MODULES. THE FIRST AND SECOND ONES ALLOW US TO TRANSFORM OPEN DATA FILES TO FORMAL CONTEXTS. IN THE THIRD MODULE, TWO IMPORTANT PROCESSES ARE PERFORMED: (I) A CHARACTERIZATION OF THE STATES OF THE SKY AND (II) AN ANALYSIS OF THE WEATHER CONDITIONS UNDER WHICH THE ENERGY PRODUCTION IS OPTIMAL.

THIS PAPER SHOWS HOW FUZZY FORMAL CONCEPT ANALYSIS CAN BE APPLIED TO A REAL CRIMES DATASET IN ORDER TO EXTRACT PATTERNS AND KNOWLEDGE FROM IT. DIFFERENT CONCEPTS AND ATTRIBUTE IMPLICATIONS HAVE BEEN SELECTED AND INTERPRETED OBTAINING INTERESTING CONSEQUENCES.

EXECUTION TRACES COMPREHENSION IS AN IMPORTANT TOPIC IN COMPUTER SCIENCE SINCE IT ALLOWS SOFTWARE ENGINEERS TO GET A BETTER UNDERSTANDING OF THE SYSTEM BEHAVIOR. HOWEVER, TRACES ARE USUALLY VERY LARGE AND HENCE THEY ARE DIFFICULT TO INTERPRET. PARALLEL, EXECUTION TRACES COMPREHENSION IS A VERY IMPORTANT TOPIC INTO THE ALGORITHMS LEARNING COURSES SINCE IT ALLOWS STUDENTS TO GET A BETTER UNDERSTANDING OF THE ALGORITHM BEHAVIOR. THEREFORE, THERE IS A NEED TO INVESTIGATE WAYS TO HELP STUDENTS (AND TEACHERS) FIND AND UNDERSTAND IMPORTANT INFORMATION CONVEYED IN A TRACE DESPITE THE TRACE BEING MASSIVE. IN THIS PAPER, WE PROPOSE A NEW APPROXIMATION FOR EXECUTION TRACES COMPREHENSION BASED ON FUZZY LINGUISTIC DESCRIPTIONS. A NEW METHODOLOGY AND A DATA-DRIVEN ARCHITECTURE BASED ON LINGUISTIC MODELLING OF COMPLEX PHENOMENON ARE PRESENTED AND EXPLAINED. IN PARTICULAR, THEY ARE APPLIED TO AUTOMATICALLY GENERATE LINGUISTIC REPORTS FROM EXECUTION TRACES GENERATED DURING THE EXECUTION OF ALGORITHM IMPLEMENTED BY THE STUDENTS OF AN INTRODUCTORY COURSE OF ARTIFICIAL INTELLIGENCE. TO THE BEST OF OUR KNOWLEDGE, IT IS THE FIRST TIME THAT LINGUISTIC MODELLING OF COMPLEX PHENOMENON IS APPLIED TO EXECUTION TRACES COMPREHENSION. THROUGHOUT THE ARTICLE, IT IS SHOWN HOW THIS KIND OF TECHNOLOGY CAN BE EMPLOYED AS A USEFUL COMPUTER-ASSISTED ASSESSMENT TOOL THAT PROVIDES STUDENTS AND TEACHERS WITH TECHNICAL, IMMEDIATE AND PERSONALISED FEEDBACK ABOUT THE ALGORITHMS THAT ARE BEING STUDIED AND IMPLEMENTED. AT THE SAME TIME, THEY PROVIDE US WITH TWO USEFUL APPLICATIONS: THEY ARE AN INDISPENSABLE PEDAGOGICAL RESOURCE FOR IMPROVING COMPREHENSION OF EXECUTION TRACES, AND THEY PLAY AN IMPORTANT ROLE IN THE PROCESS OF MEASURING AND EVALUATING THE ?BELIEVABILITY? OF THE AGENTS IMPLEMENTED. TO SHOW AND EXPLORE THE POSSIBILITIES OF THIS NEW TECHNOLOGY, A WEB PLATFORM HAS BEEN DESIGNED AND IMPLEMENTED BY ONE OF THE AUTHORS, AND IT HAS BEEN INCORPORATED INTO THE PROCESS OF ASSESSMENT OF AN INTRODUCTORY ARTIF

THIS PAPER AIMS TO PROPOSE A NEW VERSION OF THE TURING TEST FOR COMPUTER GAME BOTS BASED ON LINGUISTIC DESCRIPTION OF COMPLEX PHENOMENA AND RESTRICTED EQUIVALENCE FUNCTIONS WHOSE GOAL IS TO EVALUATE THE """"BELIEVABILITY"""" OF THE COMPUTER GAMES BOTS ACTING IN A VIRTUAL WORLD. A DATA-DRIVEN SOFTWARE ARCHITECTURE BASED ON LINGUISTIC MODELLING OF COMPLEX PHENOMENA IS ALSO PROPOSED WHICH ALLOWS US TO AUTOMATICALLY GENERATE BOTS BEHAVIOR PROFILES WHICH CAN BE COMPARED WITH HUMAN PLAYERS BEHAVIOR PROFILES IN ORDER TO PROVIDE US WITH A SIMILARITY MEASURE OF BELIEVABILITY BETWEEN THEM.

THIS PAPER AIMS TO PROPOSE A METHOD FOR AUTOMATICALLY LABELLING AN AFFECTIVE LEXICON WITH INTENSITY VALUES BY USING THE WORDNET SIMILARITY (WS) SOFTWARE PACKAGE WITH THE PURPOSE OF IMPROVING THE RESULTS OF AN AFFECTIVE ANALYSIS PROCESS, WHICH IS RELEVANT TO INTERPRETING THE TEXTUAL INFORMATION THAT IS AVAILABLE IN SOCIAL NETWORKS. THE HYPOTHESIS STATES THAT IT IS POSSIBLE TO IMPROVE AFFECTIVE ANALYSIS BY USING A LEXICON THAT IS ENRICHED WITH THE INTENSITY VALUES OBTAINED FROM SIMILARITY METRICS. ENCOURAGING RESULTS WERE OBTAINED WHEN AN AFFECTIVE ANALYSIS BASED ON A LABELLED LEXICON WAS COMPARED WITH THAT BASED ON ANOTHER LEXICON WITHOUT INTENSITY VALUES. DESIGN/METHODOLOGY/APPROACH THE AUTHORS PROPOSE A METHOD FOR THE AUTOMATIC EXTRACTION OF THE AFFECTIVE INTENSITY VALUES OF WORDS USING THE SIMILARITY METRICS IMPLEMENTED IN WS. FIRST, THE INTENSITY VALUES WERE CALCULATED FOR WORDS HAVING AN AFFECTIVE ROOT IN WORDNET. THEN, TO EVALUATE THE EFFECTIVENESS OF THE PROPOSAL, THE RESULTS OF THE AFFECTIVE ANALYSIS BASED ON A LABELLED LEXICON WERE COMPARED TO THE RESULTS OF AN ANALYSIS WITH AND WITHOUT AFFECTIVE INTENSITY VALUES.

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 THE CONCEPT OF ?-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 ?-BLOCKS EXTRACTED FROM THAT PROXIMITY RELATION CAN BE SEEN AS HIERARCHICAL SETS OF CONCEPTS GROUPED BY ABSTRACTION LEVEL. THEN, EACH GROUP (FORMING A ?-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.