Semantic technologies for industry: From knowledge modeling and integration to intelligent applications

Artificial Intelligence technologies are growingly used within several software systems ranging from Web services to mobile applications. It is by no doubt true that the more AI algorithms and methods are used the more they tend to depart from a pure "AI" spirit and end to refer to the sphere of standard software. In a sense, AI seems strongly connected with ideas, methods and tools that are not (yet) used by the general public. On the contrary, a more realistic view of it would be a rich and pervading set of successful paradigms and approaches. Industry is currently perceiving semantic technologies as a key contribution of AI to innovation. In this paper a survey of current industrial expe…

Robot passes the mirror test by inner speech

Abstract The mirror test is a well-known task in Robotics. The existing strategies are based on kinesthetic-visual matching techniques and manipulate perceptual and motion data. The proposed work attempts to demonstrate that it is possible to implement a robust robotic self-recognition method by the inner speech, i.e. the self-dialogue that enables reasoning on symbolic information. The robot self-talks and conceptually reasons on the symbolic forms of signals, and infers if the robot it sees in the mirror is itself or not. The idea is supported by the existing literature in psychology, where the importance of inner speech in self-reflection and self-concept emergence for solving the mirror…

I-ChatbIT: An intelligent chatbot for the Italian Language

A novel chatbot architecture for the Italian language is presented that is aimed at implementing cognitive under- standing of the query by locating its cor- respondent subgraph in the agent’s KB by means of a graph matching strategy pur- posely devised. The FCG engine is used for producing replies starting from the se- mantic poles extracted from the candidate answers’ subgraphs. The system imple- ments a suitable disambiguation strategy for selecting the correct answer by analyz- ing the commonsense knowledge related to the adverbs in the query that is embed- ded in the lexical constructions of the ad- verbs themselves as a proper set of fea- tures. The whole system is presented, and a com…

Toward Virtuous Machines: When Ethics Meets Robotics

In very few years, the rapid evolution in Robotics research will lead to the designing and developing of intelligent autonomous robots behaving like humans. Robots will become pervasive and soon become part of humans’ lives. Beyond the technological aspects, to reach these objectives, the researchers and the roboticists must propose novel theories and find how to implement them to allow robots to align with social, moral, and legal cues. Roboethics aims to discuss ethical problems related to the design and use of autonomous robots. It aims at defining the conduct codes to instill virtuous AI in robots. This paper aims to overview the available issues and the proposed approaches to face the …

Named Entity Recognition and Linking in Tweets Based on Linguistic Similarity

This work proposes a novel approach in Named Entity rEcognition and Linking (NEEL) in tweets, applying the same strategy already presented for Question Answering (QA) by the same authors. The previous work describes a rule-based and ontology-based system that attempts to retrieve the correct answer to a query from the DBPedia ontology through a similarity measure between the query and the ontology labels. In this paper, a tweet is interpreted as a query for the QA system: both the text and the thread of a tweet are a sequence of statements that have been linked to the ontology. Provided that tweets make extensive use of informal language, the similarity measure and the underlying processes …

ChiLab4It system in the QA4FAQ competition

ChiLab4It is the Question Answering system (QA) for Frequently Asked Questions (FAQ) developed by the Computer-Human Interaction Laboratory (ChiLab) at the University of Palermo for participating to the QA4FAQ task at EVALITA 2016 competition. The system is the versioning of the QuASIt framework developed by the same authors, which has been customized to address the particular task. This technical report describes the strategies that have been imported from QuASIt for implementing ChiLab4It, the actual system implementation, and the comparative evaluations with the results of the other participant tools, as provided by the organizers of the task. ChiLab4It was the only system whose score re…

The inner speech of the IDyOT

What robots want? Hearing the inner voice of a robot.

Summary The inner speech is thoroughly studied in humans, and it represents an interdisciplinary research issue involving psychology, neuroscience, and pedagogy. A few papers only, mostly theoretical, analyze the role of inner speech in robots. The present study investigates the potential of the robot's inner speech while cooperating with human partners. A cognitive architecture is designed and integrated with standard robot routines into a complex framework. Two threads of interaction are discussed by setting the robot operations with and without inner speech. Thanks to the robotic self-dialog, the partner can easily trace the robot's processes. Moreover, the robot can better solve conflic…

INTEGRATING ONTOLOGY AND COGNITIVE LINGUISTICS FOR NATURAL LANGUAGE PRODUCTION AND UNDERSTANDING A CASE OF STUDY IN FLUID CONSTRUCTION GRAMMAR.

VEBO: Validation of E-R diagrams through ontologies and WordNet

In the semantic web vision, ontologies are building blocks for providing applications with a high level description of the operating environment in support of interoperability and semantic capabilities. The importance of ontologies in this respect is clearly stated in many works. Another crucial issue to increase the semantic aspect of web is to enrich the level of expressivity of database related data. Nowadays, databases are the primary source of information for dynamical web sites. The linguistic data used to build the database structure could be relevant for extracting meaningful information. In most cases, this type of information is not used for information retrieval. The work present…

Automation Inner Speech as an Anthropomorphic Feature Affecting Human Trust: Current Issues and Future Directions

This paper aims to discuss the possible role of inner speech in influencing trust in human–automation interaction. Inner speech is an everyday covert inner monolog or dialog with oneself, which is essential for human psychological life and functioning as it is linked to self-regulation and self-awareness. Recently, in the field of machine consciousness, computational models using different forms of robot speech have been developed that make it possible to implement inner speech in robots. As is discussed, robot inner speech could be a new feature affecting human trust by increasing robot transparency and anthropomorphism.

An Innovative Statistical Tool for Automatic OWL-ERD Alignment

Aligning two representations of the same domain with different expressiveness is a crucial topic in nowadays semantic web and big data research. OWL ontologies and Entity Relation Diagrams are the most widespread representations whose alignment allows for semantic data access via ontology interface, and ontology storing techniques. The term ""alignment" encompasses three different processes: OWL-to-ERD and ERD-to-OWL transformation, and OWL-ERD mapping. In this paper an innovative statistical tool is presented to accomplish all the three aspects of the alignment. The main idea relies on the use of a HMM to estimate the most likely ERD sentence that is stated in a suitable grammar, and corre…

The Inner Life of a Robot in Human-Robot Teaming

Giving the robot a 'human' inner life, such as the capability to think about itself and to understand what the other team members are doing, would increase the efficiency of trustworthy interactions with the other members of the team. Our long-Term research goal is to provide the robot with a computational model of inner life helping the robot to reason about itself, its capabilities, its environment and its teammates. Robot inner speech is a part of the research goal. In this paper, we summarize the results obtained in this direction.

The inner speech of the IDyOT: Comment on “Creativity, information, and consciousness: The information dynamics of thinking” by Geraint A. Wiggins

The comment on “Creativity, information, and consciousness: The information dynamics of thinking” by Geraint A. Wiggins

QuASIt: A Cognitive Inspired Approach to Question Answering for the Italian Language

In this paper we present QuASIt, a Question Answering System for the Italian language, and the underlying cognitive architecture. The term cognitive is meant in the procedural semantics perspective, which states that the interpretation and/or production of a sentence requires the execution of some cognitive processes over both a perceptually grounded model of the world, and a linguistic knowledge acquired previously. We attempted to model these cognitive processes with the aim to make an artificial agent able both to understand and produce natural language sentences. The agent runs these processes on its inner domain representation using the linguistic knowledge also. In this sense, QuASIt …

Cognitive Linguistics as the Underlying Framework for Semantic Annotation

In recent years many attempts have been made to design suitable sets of rules aimed at extracting the semantic meaning from plain text, and to achieve annotation, but very few approaches make extensive use of grammars. Current systems are mainly focused on extracting the semantic role of the entities described in the text. This approach has limitations: in such applications the semantic role is conceived merely as the meaning of the involved entities without considering their context. As an example, current semantic annotators often specify a date entity without any annotation regarding the kind of the date itself i.e. a birth date, a book publication date, and so on. Moreover, these system…

A cognitive architecture for inner speech

Abstract A cognitive architecture for inner speech is presented. It is based on the Standard Model of Mind, integrated with modules for self-talking. Briefly, the working memory of the proposed architecture includes the phonological loop as a component which manages the exchanging information between the phonological store and the articulatory control system. The inner dialogue is modeled as a loop where the phonological store hears the inner voice produced by the hidden articulator process. A central executive module drives the whole system, and contributes to the generation of conscious thoughts by retrieving information from long-term memory. The surface form of thoughts thus emerges by …

A Hidden Markov Model for Automatic Generation of ER Diagrams from OWL Ontology

Connecting ontological representations and data models is a crucial need in enterprise knowledge management, above all in the case of federated enterprises where corporate ontologies are used to share information coming from different databases. OWL to ERD transformations are a challenging research field in this scenario, due to the loss of expressiveness arising when OWL axioms have to be represented using ERD notation. In this paper we propose an innovative technique for estimating the most likely composition of ERD constructs that correspond to a given sequence of OWL axioms. We model such a process using a Hidden Markov Model (HMM) where the OWL inputs are the observable states, while E…

Semantic sense extraction from Wikipedia pages

This paper presents a technique aimed to extract structured information from unstructured Wikipedia contents related to a particular topic, and to arrange it in a semantic way inside an ontology. The general framework is the design of an artificial agent able to deliberate when increasing its domain knowledge. In particular, this cognitive agent acts as a dialogue manager in an Intelligent Tutoring System (ITS) already presented by the authors. Our approach is based on the definition of useful patterns able to extract and identify novel concepts and relations to be added to the knowledge base. We propose a method that uses information from the wiki page’s structure. We define different stra…

Robots as intelligent assistants to face COVID-19 pandemic

AbstractMotivationThe epidemic at the beginning of this year, due to a new virus in the coronavirus family, is causing many deaths and is bringing the world economy to its knees. Moreover, situations of this kind are historically cyclical. The symptoms and treatment of infected patients are, for better or worse even for new viruses, always the same: more or less severe flu symptoms, isolation and full hygiene. By now man has learned how to manage epidemic situations, but deaths and negative effects continue to occur. What about technology? What effect has the actual technological progress we have achieved? In this review, we wonder about the role of robotics in the fight against COVID. It p…

Aligning Relational Schema and OWL Ontologies with Hidden Markov Model

The problem of bridging the gap between relational schema and ontologies is actively investigated in the Semantic Web and business communities. The main motivations are the OBDA scenario, where a domain ontology allows to hidden the technical details of the db to end-users; and the persistent storage of ontologies in db for facilitating search and retrieval keeping the benefits of DBMSs such as security and integrity. In these cases, the ABox is usually stored into a db, and the TBox is maintained in an ontology; for this reason, schema alignment is a more significant problem than the instance matching one. The use of manual mappings is hard and expensive, especially for large representatio…

HOWERD: A Hidden Markov Model for Automatic OWL-ERD Alignment

The HOWERD model for estimating the most likely alignment between an OWL ontology and an Entity Relation Diagram (ERD) is presented. Automatic alignment between relational schema and ontology represents a big challenge in Semantic Web research due to the different expressiveness of these representations. A relational schema is less expressive than the ontology; this is a non trivial problem when accessing data via an ontology and for ontology storing by means of a relational schema. Existent alignment methodologies fail in loosing some contents of the involved representations because the ontology captures more semantic information, and several elements are left unaligned. HOWERD relies on a…

INTEGRATING ONTOLOGY AND COGNITIVE LINGUISTICS FOR NATURAL LANGUAGE PRODUCTION AND UNDERSTANDING

Ontologies have been designed to capture the semantic knowledge of a domain in a machine understandable form. Current standards for managing ontologies like OWL are lacking in linguistic grounding, and are not able to achieve a clear link with natural language. Bridging this gap, unskilled users could be able to infer the information described in the ontology and it would be possible either producing or parsing utterances about the represented domain automatically. Moreover, as in the case of enterprises, it could be very useful to extract information from external documental corpora that are related to the same domain. Many attempts have been made with the aim to create a natural language …

An A* Based Semantic Tokenizer for Increasing the Performance of Semantic Applications

Semantic Applications (SAs) makes use of ontolo- gies and their performance can depend on the syntactic labels of the modeled entities; even if several approaches have been devised to formalize ontologies, no formal approaches have been devised for naming their constituents, which look as long word concatenations without any particular separation. We present a novel semantic tokenizer that finds the sub-words through an application of the A* based search algorithm; the A* functions rely on a set of linguistic criteria and on the meta-cognitive perspective of the activity of reading.

Knowledge acquisition through introspection in Human-Robot Cooperation

Abstract When cooperating with a team including humans, robots have to understand and update semantic information concerning the state of the environment. The run-time evaluation and acquisition of new concepts fall in the critical mass learning. It is a cognitive skill that enables the robot to show environmental awareness to complete its tasks successfully. A kind of self-consciousness emerges: the robot activates the introspective mental processes inferring if it owns a domain concept or not, and correctly blends the conceptual meaning of new entities. Many works attempt to simulate human brain functions leading to neural network implementation of consciousness; regrettably, some of thes…

Robot's Inner Speech Effects on Trust and Anthropomorphic Cues in Human-Robot Cooperation

Inner Speech is an essential but also elusive human psychological process which refers to an everyday covert internal conversation with oneself. We argue that programming a robot with an overt self-talk system, which simulates human inner speech, might enhance human trust by improving robot transparency and anthropomorphism. For this reasons, this work aims to investigate if robot’s inner speech, here intended as overt self-talk, affects human trust and anthropomorphism when human and robot cooperate. A group of participants was engaged in collaboration with the robot. During cooperation, the robot talks to itself. To evaluate if the robot’s inner speech influences human trust, two question…

Acquisition of New Knowledge to Manage Conversation in TutorJ

This paper presents new conversation modules developed for TutorJ to support the use of meta-cognitive strategies in the learners. TutorJ is an Intelligent Tutoring System able to interact with users to assess their skills, and improve their knowledge in a specific domain. New models are devoted to plan the conversation and to acquire new knowledge from semi-structured data sources. Conversation planning is based on probabilistic techniques. Knowledge acquisition is based on retrieval, transformation and alignment of data from wikis to enrich the replies to students questions.

Fostering Teacher-Student Interaction and Learner Autonomy by the I-TUTOR Maps

The paper analyses the use of an automatically generated map as a mediator; that map visually represents the study domain of a university course and fosters the co-activity between teachers and stu- dents. In our approach the role of the teacher is meant as a media- tor between the student and knowledge. The mediation (and not the transmission) highlights a process in which theres no deterministic rela- tion between teaching and learning. Learning is affected by the students previous experiences, their own modalities of acquisition and by the in- puts coming from the environment. The learning path develops when the teachers and the students visions approach and, partly, overlap. In this cas…

Developing Self-Awareness in Robots via Inner Speech

The experience of inner speech is a common one. Such a dialogue accompanies the introspection of mental life and fulfills essential roles in human behavior, such as self-restructuring, self-regulation, and re-focusing on attentional resources. Although the underpinning of inner speech is mostly investigated in psychological and philosophical fields, the research in robotics generally does not address such a form of self-aware behavior. Existing models of inner speech inspire computational tools to provide a robot with this form of self-awareness. Here, the widespread psychological models of inner speech are reviewed, and a cognitive architecture for a robot implementing such a capability is…

Robot’s Inner Speech Effects on Human Trust and Anthropomorphism

AbstractInner Speech is an essential but also elusive human psychological process that refers to an everyday covert internal conversation with oneself. We argued that programming a robot with an overt self-talk system that simulates human inner speech could enhance both human trust and users’ perception of robot’s anthropomorphism, animacy, likeability, intelligence and safety. For this reason, we planned a pre-test/post-test control group design. Participants were divided in two different groups, one experimental group and one control group. Participants in the experimental group interacted with the robot Pepper equipped with an over inner speech system whereas participants in the control …

A Cognitive Dialogue Manager for Education Purposes

A conversational agent is a software system that is able to interact with users in a natural way, and often uses natural language capabilities. In this chapter, an evolution of a conversational agent is presented according to the definition of dialogue management techniques for the conversational agents. The presented conversational agent is intended to act as a part of an educational system. The chapter outlines the state-of-the-art systems and techniques for dialogue management in cognitive educational systems, and the underlying psychological and social aspects. We present our framework for a dialogue manager aimed to reduce the uncertainty in users’ sentences during the assessment of hi…

WikiArt: An Ontology-Based Information Retrieval System for Arts

The paper presents WikiArt, a new system integrating three distinct types of contents about the art: data, information, and knowledge, to generate automatically thematic paths to consult all its contents. WikiArt is a wiki, allowing to manage cooperatively documents about artists, artworks, artistic movements or techniques, and so on. It is also an expert system, provided with an ontology about arts, with which it is able to plan possible different ways of consulting and browsing its contents. This ability is made possible by a second part of the ontology of the system, describing a collection of criteria regarding how to plan thematic paths, and by a set of rules followed by the expert sys…