Università degli Studi di Napoli "Parthenope"

Teaching schedule

Academic year: 
2020/2021
Belonging course: 
Course of Master's Degree Programme on APPLIED COMPUTER SCIENCE (MACHINE LEARNING AND BIG DATA)
Disciplinary sector: 
INFORMATICS (INF/01)
Language: 
English
Credits: 
6
Year of study: 
2
Teachers: 
MELE Francesco
Cycle: 
Second semester
Hours of front activity: 
48

Language

English

Course description

During the course, the student will acquire skills for the representation of various domains of knowledge by referring to basic representation techniques of spatial, temporal and causal reasoning. During the course, the student will learn the principles and techniques of semantic annotation. The goal is to acquire skills in representing knowledge by taking cultural stories present on the WEB as example material.
The aim of the course is to be able to model actions and events for both external scenarios and internal mental action in the robotic field. Finally, the possibility of enabling the student to build chatbots for natural language is another objective of the course.

Prerequisites

Syllabus

1 Knowledge representation
-Introduction to functional, structural, behavioral, empirical representations
- Introduction to ontologies.
TOOLS - Logic programming - Introduction to Prolog - Introduction to Answer Set Programming (ASP). Protege and plugin for managing ontologies.
2 Representation of spatial relationships
- Quantitative spatial relations, qualitative spatial relations
- Part-totality relationship, types of meronomic relationships and criteriality
- Axiomatics for spatial reasoning - Examples of applications.
TOOLS - Taxonomy of spatial relations in Asp - Spatial reasoning rules in Asp.
3 Functional - structural - behavioral representations
TOOLS - Functional, structural and behavioral taxonomies in Asp.

4 Temporal representation
-Time as a succession, duration and perspective
- Temporal and causal axiomatics
- Events and their components through an ontological approach,
-A what, where, when, who and why model for events
TOOLS - Axiomatics of Russel & Kamp, Axiomatics of Event Calculus (in ASP), Axiomatics of causal reasoning in Prolog and Asp.

5- Rational agents
-Represent agents, the DBI model (Desire, Belief, Intention)
-Communication between agents
-Cognitive models - criteria for the construction of cognitive models
TOOLS - Emotional models of cognitive agents in ASP.
6- Introduction to semantic annotation
- The annotation of events, properties, roles, mental events and causal relationships.
- The annotation of compound events, representations of stories and connectivity of events
TOOLS - CSWL (Cultural Story Web Language) a language for annotating cultural stories on the web based on Asp.
7 Multimedia presentations
- Principles of multimedia presentation
- Syncretic discourse, its components and semantic isotopies
- Semantic Mashup and event-based storytelling
TOOLS A mashup method for the production of cultural audiovisuals.

8- Natural Language Processing (NLP)
-Applications of NLP techniques
-Parsing and Parser
-Tools for discovering names, actions, time expressions and events in NL.
9- Introduction to chatbots
TOOLS - AIML, Ide for chatbots

The program provides an introduction to the representation of knowledge, in particular to those that contain spatial and temporal relationships.There will be an introduction to Mathematical Logic. A broad introduction to logic programming is also provided, with lessons that include exercises on the Prolog language and on Answer Set Programming.
A part dedicated to semantic annotation will follow. To this end, the CSWL language will be presented with which, starting from natural language texts, events, components of events, properties, roles, mental events, causal relationships and stories can be formally noted. Various axioms related to spatial, temporal and causal reasoning will be presented. Special case will construct the presentation of a version of Event Calculus for the simulation of mental causation - useful techniques for modeling rational agents. The final part of the course will cover techniques for natural language processing, with particular attention to chatbot construction techniques.

Teaching Methods

Textbooks

-A Dovier, A. Formisano, Programmazione Dichiarativa in Prolog, CLP e ASP.
-Muller, E. (2015). Commonsense reasoning (second edition). Morgan Kaufmann.
- Stuart Russell, Peter Norvig. Artificial Intelligence: A Modern Approach, Global Edition, 4th Edition,
- F. Mele, A. Sorgente CSWL - Un formalismo per rappresentare storie culturali nel Web, I. R. CNR-ISASI 180/15 09 Marzo 2015
-L. Bordoni, F. Mele, A. Sorgente, Artificial Intelligence for Cultural Heritage, Cambridge Scholars Publishing, 2016
-Mele F., Sorgente A., Semantic mashups of multimedia cultural stories, Intelligenza Artificiale Journal IOS Press, Issue Volume 6, Number 1 / 2012 pag. 19-40
-For the exercises regarding ASP, the ASPIDE platform will be used, available on the website of the University of
Calabria ASPIDE (unical.it)

Learning assessment

During the course, students will be required to solve some case studies. For the final exam of the course, a project will be assigned that will involve almost all the topics presented in the lessons.

More information