APPLICATIONS FOR AUTOMATIC KNOWLEDGE REPRESENTATION

Mario MONTELEONE APPLICATIONS FOR AUTOMATIC KNOWLEDGE REPRESENTATION

SC23100019
DEPARTMENT OF POLITICAL AND COMMUNICATION SCIENCES
EQF7
CORPORATE COMMUNICATION, MARKETING INNOVATION AND DIGITAL MEDIA
2025/2026

OBBLIGATORIO
YEAR OF COURSE 1
YEAR OF DIDACTIC SYSTEM 2025
AUTUMN SEMESTER
CFUHOURSACTIVITY
640LESSONS
Objectives
WITH REFERENCE TO THE RESEARCH ACTIVITIES CARRIED OUT IN THE FIELD OF KNOWLEDGE AUTOMATIC REPRESENTATION IN DIGITAL HUMANITIES, AND MORE IN DETAIL OF NATURAL LANGUAGE PROCESSING, THE COURSE PROVIDES FOR INTRODUCING STUDENTS TO THE KNOWLEDGE OF SOFTWARE, ENVIRONMENTS, TOOLS, LANGUAGES, CODES AND APPLICATIONS USED TODAY IN THE FIELD OF AUTOMATIC KNOWLEDGE MANAGEMENT THROUGH NATURAL LANGUAGE (COMPUTATIONAL LINGUISTICS).
Prerequisites
A GOOD KNOWLEDGE OF GENERAL LINGUISTICS IS REQUIRED.
Contents
THE COURSE INTENDS TO INTRODUCE STUDENTS TO THE KNOWLEDGE OF SOFTWARE, ENVIRONMENTS, TOOLS, LANGUAGES, CODES AND APPLICATIONS USED TODAY IN THE FIELD OF AUTOMATIC KNOWLEDGE MANAGEMENT THROUGH NATURAL LANGUAGE (COMPUTATIVE LINGUISTICS). FURTHERMORE, THE COURSE WILL TRAIN STUDENTS IN THE KNOWLEDGE AND UNDERSTANDING OF CURRENT AND PAST TOPICS IN TERMS OF THOSE APPLICATION RESEARCH THAT HAVE LED AND ARE LED TO THE PRACTICAL USE OF SOFTWARE AND AUTOMATIC ROUTINES IN THE FIELD OF AUTOMATIC KNOWLEDGE REPRESENTATION, IN DIGITAL HUMANITIES IN THE BROADEST SENSE OF THE TERM. THE COURSE AIMS TO LEAD THE STUDENT TO KNOW AND UNDERSTAND THE APPLICATIONS AND USES OF SOFTWARE, ENVIRONMENTS, TOOLS, LANGUAGES, CODES AND APPLICATIONS USED TODAY IN THE FIELD OF AUTOMATIC REPRESENTATION OF KNOWLEDGE IN DIGITAL HUMANITIES AS WELL AS IN ARTIFICIAL INTELLIGENCE AND THROUGH COMPUTATIONAL LINGUISTICS. THE MAIN PICS WILL BE DIVIDED ON THE BASIS OF THE ENGINEERING CHARACTERISTICS AND THE METHODOLOGICAL SCOPE OF REFERENCE, AS WELL AS ON WHETHER THEY ARE RULE-BASED (BASED ON THE FORMALIZATION OF MORPHOSYNTACTIC RULES) OR RULE-LESS (NOT BASED ON THE FORMALIZATION OF MORPHOSYNTACTIC RULES). GREAT IMPORTANCE WILL ALSO BE GIVEN TO THE DEVELOPMENT OF FORMALIZED LINGUISTIC RESOURCES. IN THIS SENSE, THEIR ENGINEERING CHARACTERISTICS AND THE METHODOLOGICAL SCOPE OF REFERENCE WILL BE ILLUSTRATED. FINALLY, STUDENTS WILL BE GUIDED IN THE KNOWLEDGE AND PRACTICAL USE OF A SPECIFIC NLP SOFTWARE ENVIRONMENT, AND OF THE LINGUISTICS USED BY IT, (ELECTRONIC DICTIONARIES AND FORMAL GRAMMARS IN THE FORM OF FINITE STATE AUTOMATA).
IN THE CONTEXT OF AUTOMATIC KNOWLEDGE REPRESENTATION IN DIGITAL HUMANITIES AS WELL AS IN ARTIFICIAL INTELLIGENCE, THE COURSE AIMS TO TRAIN STUDENTS IN MAKING INDEPENDENT JUDGMENTS ON THE ADVANCED USE OF RULE-BASED SOFTWARE, AS OPPOSED TO THOSE OF COMPUTATIONAL STATISTICS, IN ORDER TO EVALUATE THE MERITS AND LIMITATIONS OF EACH, THROUGH CRITICAL ANALYSES, AS WELL AS EVALUATIONS AND SYNTHESIS OF NEW AND COMPLEX IDEAS.
STUDENTS WILL BE LED TO COMMUNICATE AND COMPARE WHAT THEY HAVE LEARNED WITH THEIR COLLEAGUES, AS WELL AS, IN BROADER TERMS, WITH ALL SECTORS OF STUDY, RESEARCH AND COMMUNICATION THAT DEAL, IN THEIR DIFFERENT WAYS, WITH THE TOPIC OF SOFTWARE AND AUTOMATIONS USED FOR THE AUTOMATIC REPRESENTATION OF KNOWLEDGE IN DIGITAL HUMANITIES AS WELL AS IN ARTIFICIAL INTELLIGENCE.
STUDENTS WILL BE LED TO PRODUCE NEW THOUGHTS AND IDEAS RELATING TO THE CREATION AND USE OF NEW TYPES OF SOFTWARE AND AUTOMATIC ROUTINES FOR THE AUTOMATIC REPRESENTATION OF KNOWLEDGE IN DIGITAL HUMANITIES AS WELL AS IN ARTIFICIAL INTELLIGENCE, TO BE PROMOTED, USED AND TESTED ESPECIALLY WITHIN THEIR FUTURE WORK ACTIVITIES.


Teaching Methods
FRONTAL LESSONS.
Verification of learning
PROFICIENCY EXAM. THE PROFICIENCY EXAM IS HELD IN ORAL FORM. THE ORAL EXAM CONSISTS OF AN INTERVIEW, BASED ON QUESTIONS AND A DISCUSSION ON THE THEORETICAL AND METHODOLOGICAL CONTENTS INDICATED IN THE PROGRAM, AS WELL AS ON AN APPLIED-RESEARCH PROJECT, DEVELOPED AUTONOMOUSLY BY THE STUDENTS OR IN A GROUP. THE PURPOSE IS TO ASCERTAIN NOT ONLY THE LEVEL OF KNOWLEDGE AND THE ABILITY TO UNDERSTAND ACHIEVED BY THE STUDENTS, BUT ALSO THE ABILITY TO PRESENT THE TOPICS USING THE MOST APPROPRIATE TERMINOLOGY.
Texts
HANDOUTS AND TEXTS TO BE DEFINED DURING FRONTAL LESSONS.
More Information
NONE.
Lessons Timetable

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