Detection of User Activities in Intelligent Environments

Research on Ambient Intelligence (AmI) focuses on the development of smart environments adaptable to the needs and preferences of their inhabitants. For this reason it is important to understand and model user preferences. In this chapter we describe a system to detect user behavior patterns in an intelligent workplace. The system is designed for a workplace equipped in the context of Sensor9k, a project carried out at the Department of Computer Science at the University of Palermo (Italy). © Springer International Publishing Switzerland 2014.

Social robots and therapeutic adherence: a new challenge in pediatric asthma?

Social Robots are used in different contexts and, in healthcare, they are better known as Socially Assistive Robots. In the context of asthma, the use of Socially Assistive Robots has the potential to increase motivation and engagement to treatment. Other positive roles proposed for Socially Assistive Robots are to provide education, training regarding treatments, and feedback to patients. This review evaluates emerging interventions for improving treatment adherence in pediatric asthma, focusing on the possible future role of social robots in the clinical practice.

A word prediction methodology for automatic sentence completion

Word prediction generally relies on n-grams occurrence statistics, which may have huge data storage requirements and does not take into account the general meaning of the text. We propose an alternative methodology, based on Latent Semantic Analysis, to address these issues. An asymmetric Word-Word frequency matrix is employed to achieve higher scalability with large training datasets than the classic Word-Document approach. We propose a function for scoring candidate terms for the missing word in a sentence. We show how this function approximates the probability of occurrence of a given candidate word. Experimental results show that the proposed approach outperforms non neural network lang…

Chat Agents Tutoring System

In this paper we present a Multi Agent tutoring dialogue system. The Chat Agent Tutoring System is an attempt to produce incremental gains in learning using a community of chat agents, which have specific competences and are able to carry out natural language conversation. The system has been developed by integrating two emerging technologies: Java Agent Development Environment (JADE) and ALICE technology.

Sub-symbolic Mapping of Cyc Microtheories in Data-Driven “Conceptual” Spaces

The presented work aims to combine statistical and cognitive-oriented approaches with symbolic ones so that a conceptual similarity relationship layer can be added to a Cyc KB microtheory. Given a specific microtheory, a LSA-inspired conceptual space is inferred from a corpus of texts created using both ad hoc extracted pages from the Wikipedia repository and the built-in comments about the concepts of the specific Cyc microtheory. Each concept is projected in the conceptual space and the desired layer of subsymbolic relationships between concepts is created. This procedure can help a user in finding the concepts that are "sub-symbolically conceptually related" to a new concept that he want…

MODULAR KNOWLEDGE REPRESENTATION IN ADVISOR AGENTS FOR SITUATION AWARENESS

A modular knowledge representation framework for conversational agents is presented. The approach has been realized to suit the situation awareness paradigm. The modularity of the framework makes possible the composition of specific modules that deal with particular features, simplifying both the chatbot design process and its smartness. As a proof of concepts we have developed a modular, situation awareness oriented, KB for a conversational agent, which plays the role of an advisor aimed at helping a user to be in charge of a virtual town, inspired to the SimCity series game. The agent makes an extensive use of semantic computing techniques and is able to perceive, comprehend and project c…

A Geometric Algebra Based Distributional Model to Encode Sentences Semantics

Word space models are used to encode the semantics of natural language elements by means of high dimensional vectors [23]. Latent Semantic Analysis (LSA) methodology [15] is well known and widely used for its generalization properties. Despite of its good performance in several applications, the model induced by LSA ignores dynamic changes in sentences meaning that depend on the order of the words, because it is based on a bag of words analysis. In this chapter we present a technique that exploits LSA-based semantic spaces and geometric algebra in order to obtain a sub-symbolic encoding of sentences taking into account the words sequence in the sentence. © 2014 Springer-Verlag Berlin Heidel…

Exploiting multimodality for intelligent mobile access to pervasive services in cultural heritage sites

In this chapter the role of multimodality in intelligent, mobile guides for cultural heritage environments is discussed. Multimodal access to information contents enables the creation of systems with a higher degree of accessibility and usability. A multimodal interaction may involve several human interaction modes, such as sight, touch and voice to navigate contents, or gestures to activate controls. We first start our discussion by presenting a timeline of cultural heritage system evolution, spanning from 2001 to 2008, which highlights design issues such as intelligence and context-awareness in providing information. Then, multimodal access to contents is discussed, along with problems an…

Exploiting Cognitive Architectures to design Storytelling Activities for NarRob

In this work, we exploited the potential of a cognitive architecture to model the characters of a story in an interactive storytelling system. The system is accessible through NarRob, a humanoid social robot, able to manage storytelling activities aimed at improving the emotional and social skills of children, also adding expressiveness to the narration by using proper associate gestures and emotional expressions. Our main goal was to implement the cognitive processes of the agents interpreted by the robot within an environment coinciding with a narrative context. The narrated story is largely inspired by the "FearNot!" game, where in our system, we modeled the cognitive processes elaborate…

A Multimodal Guide for the Augmented Campus

The use of Personal Digital Assistants (PDAs) with ad-hoc built-in information retrieval and auto-localization functionalities can help people navigating an environment in a more natural manner compared to traditional audio/visual pre-recorded guides. In this work we propose and discuss a user-friendly, multi-modal guide system for pervasive context-aware service provision within augmented environments. The proposed system is adaptable to the user needs of mobility within a given environment; it is usable on different mobile devices and in particular on PDAs, which are used as advanced adaptive HEI (human-environment interaction) interfaces. An information retrieval service is provided that…

An Intelligent Multimodal Site-guide for the “Parco Archeologico della Valle dei Templi” in Agrigento

Creation and cognition for humanoid live dancing

Abstract Computational creativity in dancing is a recent and challenging research field in Artificial Intelligence and Robotics. We present a cognitive architecture embodied in a humanoid robot capable to create and perform dances driven by the perception of music. The humanoid robot is able to suitably move, to react to human mate dancers and to generate novel and appropriate sequences of movements. The approach is based on a cognitive architecture that integrates Hidden Markov Models and Genetic Algorithms. The system has been implemented on a NAO robot and tested in public setting-up live performances, obtaining positive feedbacks from the audience.

Geometric Algebra Rotors for Sub-Symbolic Coding of Natural Language Sentences

A sub-symbolic encoding methodology for natural language sentences is presented. The procedure is based on the creation of an LSA-inspired semantic space and associates rotation operators derived from Geometric Algebra to word bigrams of the sentence. The operators are subsequently applied to an orthonormal standard basis of the created semantic space according to the order in which words appear in the sentence. The final rotated basis is then coded as a vector and its orthogonal part constitutes the sub-symbolic coding of the sentence. Preliminary experimental results for a classification task, compared with the traditional LSA methodology, show the effectiveness of the approach.

A Kinect-Based Gesture Acquisition and Reproduction System for Humanoid Robots

The paper illustrates a system that endows an humanoid robot with the capability to mimic the motion of a human user in real time, serving as a basis for further gesture based human-robot interactions. The described approach uses the Microsoft Kinect as a low cost alternative to expensive motion capture devices.

Chatbots as Interface to Ontologies

Chatbots are simple conversational agents using 'pattern matching rules' to carry out the dialogue with the user and various expedients to improve their credibility. However, the rules on which they are based on are too restrictive and their language understanding capability is very limited. Nevertheless chatbots are widespread in several applications, especially to provide information to users in a new and enjoyable way. In this chapter we describe different chatbot architectures, exploiting the use of ontologies in order to create clever information suppliers overcoming the main limits of chatbots: The knowledge base building and the rigidness of the dialogue mechanism. © Springer Interna…

A Multimodal Interaction Guide for Pervasive Services Access

A pervasive, multimodal virtual guide for a cultural heritage site tour is illustrated. The guide is based on the integration of different technologies such as conversational agents, commonsense reasoning knowledge bases, multimodal interfaces and self-location detection systems. The aim of the work is to offer a more natural, context sensitive access to information with respect to traditional audio/visual pre-recorded guides. A prototype has been developed and implemented on a Qtek 9090 with Windows Mobile 2003 in order to deal with the "Museo Archeologico Regionale di Agrigento" domain.

Geometric Algebra Rotors for Sub-symbolic Coding of Natural Language Sentences

A sub-symbolic encoding methodology for natural language sentences is presented. The procedure is based on the creation of an LSA-inspired semantic space and associates rotation operators derived from Geometric Algebra to word bigrams of the sentence. The operators are subsequently applied to an orthonormal standard basis of the created semantic space according to the order in which words appear in the sentence. The final rotated basis is then coded as a vector and its orthogonal part constitutes the sub-symbolic coding of the sentence. Preliminary experimental results for a classification task, compared with the traditional LSA methodology, show the effectiveness of the approach.

Sub-Symbolic Knowledge Representation for Evocative Chat-Bots

A sub-symbolic knowledge representation oriented to the enhancement of chat bot interaction is proposed. The result of the technique is the introduction of a semantic sub-symbolic layer to a traditional ontology-based knowledge representation. This layer is obtained mapping the ontology concepts into a semantic space built through Latent Semantic Analysis (LSA) technique and it is embedded into a conversational agent. This choice leads to a chat-bot with “evocative” capabilities whose knowledge representation framework is composed of two areas: the rational and the evocative one. As a standard ontology we have chosen the well-founded WordNet lexical dictionary, while as chat-bot the ALICE a…

Exploiting Correlation between Body Gestures and Spoken Sentences for Real-time Emotion Recognition

Humans communicate their affective states through different media, both verbal and non-verbal, often used at the same time. The knowledge of the emotional state plays a key role to provide personalized and context-related information and services. This is the main reason why several algorithms have been proposed in the last few years for the automatic emotion recognition. In this work we exploit the correlation between one's affective state and the simultaneous body expressions in terms of speech and gestures. Here we propose a system for real-time emotion recognition from gestures. In a first step, the system builds a trusted dataset of association pairs (motion data -> emotion pattern), a…

An Emotional Talking Head for a Humoristic Chatbot

The interest about enhancing the interface usability of applications and entertainment platforms has increased in last years. The research in human-computer interaction on conversational agents, named also chatbots, and natural language dialogue systems equipped with audio-video interfaces has grown as well. One of the most pursued goals is to enhance the realness of interaction of such systems. For this reason they are provided with catchy interfaces using humanlike avatars capable to adapt their behavior according to the conversation content. This kind of agents can vocally interact with users by using Automatic Speech Recognition (ASR) and Text To Speech (TTS) systems; besides they can c…

A Decisional Multi-Agent Framework for Automatic Supply Chain Arrangement

In this work, a multi-agent system (MAS) for supply chain dynamic configuration is proposed. The brain of each agent is composed of a Bayesian Decision Network (BDN); this choice allows the agent for taking the best decisions estimating benefits and potential risks of different strategies, analyzing and managing uncertain information about the collaborating companies. Each agent collects information about customer's orders and current market prices, and analyzes previous experiences of collaborations with trading partners. The agent therefore performs a probabilistic inferential reasoning to filter information modeled in its knowledge base in order to achieve the best performance in the sup…

An Intelligent Agent to Support City Policies Decisions

Creativity in Conceptual Spaces

The main aim of this paper is contributing to what in the last few years has been known as computational creativity. This will be done by showing the relevance of a particular mathematical representation of G"ardenfors's conceptual spaces to the problem of modelling a phenomenon which plays a central role in producing novel and fruitful representations of perceptual patterns: analogy.

An Approach to Enhance Chatbot Semantic Power and Maintainability: Experiences within the FRASI Project

The paper illustrates the implementation and semantic enhancement of a domain-oriented Question-Answering system based on a pattern-matching chat bot technology, developed within an industrial project, named FRASI. The main difficulty in building a KB for a chat bot is to handwrite all possible question-answer pairs that constitute the KB. The proposed approach simplifies the chat bot realization thanks to two solutions. The first one uses an ontology, which is exploited in a twofold manner: to construct dynamic answers as a result of an inference process about the domain, and to automatically populate, off-line, the chat bot KB with sentences that can be derived from the ontology, describi…

Semantic Word Error Rate for Sentence Similarity

Sentence similarity measures have applications in several tasks, including: Machine Translation, Paraphrase Iden- tification, Speech Recognition, Question-answering and Text Summarization. However, measures designed for these tasks are aimed at assessing equivalence rather than resemblance, partly departing from human cognition of similarity. While this is reasonable for these activities, it hinders the applicability of sentence similarity measures to other tasks. We therefore propose a new sentence similarity measure specifically designed for resemblance evaluation, in order to cover these fields better. Experimental results are discussed.

Body Gestures and Spoken Sentences: A Novel Approach for Revealing User’s Emotions

In the last decade, there has been a growing interest in emotion analysis research, which has been applied in several areas of computer science. Many authors have con- tributed to the development of emotion recognition algorithms, considering textual or non verbal data as input, such as facial expressions, gestures or, in the case of multi-modal emotion recognition, a combination of them. In this paper, we describe a method to detect emotions from gestures using the skeletal data obtained from Kinect-like devices as input, as well as a textual description of their meaning. The experimental results show that the correlation existing between body movements and spoken user sentence(s) can be u…

Social Practices based characters in a Robotic Storytelling System

In this work, we present a robotic storytelling system, where the characters have been modelled as cognitive agents embodied in Pepper and NAO robots. The characters have been designed by exploiting the ACT-R architecture, taking into account knowledge, behaviours, norms, and expectations typical of social practices and desires resulting from their personality. The characters explain their reasoning processes during the narration, through a sort of internal dialogue that generate a high level of credibility experienced over the audience.

Sensor Mining for User Behavior Profiling in Intelligent Environments

The proposed system exploits sensor mining methodologies to profile user behaviors patterns in an intelligent workplace. The work is based in the assumption that users’ habit profiles are implicitly described by sensory data, which explicitly show the consequences of users’ actions over the environment state. Sensor data are analyzed in order to infer relationships of interest between environmental variables and the user, detecting in this way behavior profiles. The system is designed for a workplace equipped in the context of Sensor9k, a project carried out at the Department of Computer Science of Palermo University.

Virtual conversation with a real talking head

A talking head is system performing an animated face model synchronized with a speech synthesis module. It is used as a presentation layer of a conversational Agent which provide an answer. It provides an answer when a query is written as an input by the user. The textual answer is converted into facial movements of a 3D face model whose lips and tongue movements are synchronized with the sound of the synthetic voice. The Client-Server paradigm has been used for the WEB infrastructure delegating the animation and synchronization to the client, so that the server can satisfy multiple requests from clients; while the Chatbot, the Digital Signal Processing and the Natural language Processing a…

An Artificial Soft Somatosensory System for a Cognitive Robot

The paper proposes an artificial somatosensory system loosely inspired by human beings' biology and embedded in a cognitive architecture (CA). It enables a robot to receive the stimulation from its embodiment, and use these sensations, we called roboceptions, to behave according to both the external environment and the internal robot status. In such a way, the robot is aware of its body and able to interpret physical sensations can be more effective in the task while maintaining its well being. The robot's physiological urges are tightly bound to the specific physical state of the robot. Positive and negative physical information can, therefore, be processed and let the robot behave in a mo…

Clifford Rotors for Conceptual Representation in Chatbots

In this abstract we introduce an unsupervised sub-symbolic natural language sentences encoding procedure aimed at catching and representing into a Chatbot Knowledge Base (KB) the concepts expressed by an user interacting with a robot. The chatbot KB is coded in a conceptual space induced from the application of the Latent Semantic Analysis (LSA) paradigm on a corpus of documents. LSA has the effect of decomposing the original relationships between elements into linearly-independent vectors. Each basis vector can be considered therefore as a "conceptual coordinate", which can be tagged by the words which better characterize it. This tagging is obtained by performing a (TF-IDF)-like weighting…

A Modular Framework for Versatile Conversational Agent Building

This paper illustrates a web-based infrastructure of an architecture for conversational agents equipped with a modular knowledge base. This solution has the advantage to allow the building of specific modules that deal with particular features of a conversation (ranging from its topic to the manner of reasoning of the chatbot). This enhances the agent interaction capabilities. The approach simplifies the chatbot knowledge base design process: extending, generalizing or even restricting the chatbot knowledge base in order to suit it to manage specific dialoguing tasks as much as possible.

A Modular Architecture for Adaptive ChatBots

We illustrate an architecture for a conversational agent based on a modular knowledge representation. This solution provides intelligent conversational agents with a dynamic and flexible behavior. The modularity of the architecture allows a concurrent and synergic use of different techniques, making it possible to use the most adequate methodology for the management of a specific characteristic of the domain, of the dialogue, or of the user behavior. We show the implementation of a proof-of-concept prototype: a set of modules exploiting different knowledge representation techniques and capable to differently manage conversation features has been developed. Each module is automatically trigg…

MAGA: A Mobile Archaeological Guide at Agrigento

An algebra for the manipulation of conceptual spaces in cognitive agents

According to Gärdenfors, the theory of conceptual spaces describes a level of representation present in some cognitive agents between a sub-conceptual and a symbolic level of representation. In contrast to a large part of contemporary philosophical speculation on these matters for which concepts and conceptual content are propositional, conceptual spaces provide a geometric framework for the representation of concepts. In this paper we introduce an algebra for the manipulation of different conceptual spaces in order to formalise the process whereby an artificial agent rearranges its internal conceptual representations as a consequence of its perceptions, which are here rendered in terms of …

A Robotic Humanoid for Information Exploration on Cultural Heritage Domain

The work presented here illustrates an humanoid robot capable of interacting with an human user within the Cultural Heritage domain. Two different and complementary AI approaches, namely sub-symbolic and symbolic, have been implemented and combined together to design the framework of a robot having both rational and intuitive capabilities. Furthermore, the robot is capable of providing information expressively and of adapting its behavior according to the emotional content of the artworks descriptions. This could make the robot more effective in providing information and entertaining the users.

Una comunità di Chat-bot per i beni culturali - Expert Chat-Bots for Cultural Heritage

Interacting with Augmented Environments

Pervasive systems augment environments by integrating information processing into everyday objects and activities. They consist of two parts: a visible part populated by animate (visitors, operators) or inanimate (AI) entities interacting with the environment through digital devices, and an invisible part composed of software objects performing specific tasks in an underlying framework. This paper shows an ongoing work from the University of Palermo''s Department of Computer Science and Engineering that addresses two issues related to simplifying and broadening augmented environment access.

Roboception and adaptation in a cognitive robot

In robotics, perception is usually oriented at understanding what is happening in the external world, while few works pay attention to what is occurring in the robot’s body. In this work, we propose an artificial somatosensory system, embedded in a cognitive architecture, that enables a robot to perceive the sensations from its embodiment while executing a task. We called these perceptions roboceptions, and they let the robot act according to its own physical needs in addition to the task demands. Physical information is processed by the robot to behave in a balanced way, determining the most appropriate trade-off between the achievement of the task and its well being. The experiments show …

A Conversational Agent to Support Decisions in SimCity like Games

Computational intelligent techniques applied to economics have played an important role in the last years. In this paper we propose a framework based on an intelligent conversational agent embedded with a decision support system, aimed at suggesting the best managing strategies for a game-based model of a virtual town. The agent tries to prospect the future evolutions of particular choices taken by the user. Interaction is conducted through a natural language interface built as an Alice-based conversational agent.

Intelligent Advisor Agents in Distributed Environments

The chapter presents a Distributed Expert System based on a multi-agent-architecture. The system is composed of a community of intelligent conversational agents playing the role of specialized advisors for the government of a virtual town, inspired to the SimCity game. The agents are capable to handle strategic decision under uncertainty conditions. They interact in natural language with their owners, obtain information on the current status of the town and give suggestions about the best strategies to apply in order to govern the town. © 2010 Springer-Verlag Berlin Heidelberg.

A Semantic Layer on Semi-structured Data Sources for Intuitive Chatbots

The main limits of chatbot technology are related to the building of their knowledge representation and to their rigid information retrieval and dialogue capabilities, usually based on simple "pattern matching rules". The analysis of distributional properties of words in a texts corpus allows the creation of semantic spaces where represent and compare natural language elements. This space can be interpreted as a "conceptual" space where the axes represent the latent primitive concepts of the analyzed corpus. The presented work aims at exploiting the properties of a data-driven semantic/conceptual space built using semi-structured data sources freely available on the web, like Wikipedia. Thi…

An RFID framework for multimodal service provision

In recent years there has been a growing interest toward the development of pervasive and context-aware services, and RFID technology played a relevant role in the context sensing task. We propose the use of RFID technology together with a conversational agent in order to implement a multimodal information retrieval service we call SensorMesh. The information acquired from RFID tags about the nearest point of interest is processed by the conversational agent that carries a more natural interaction with the user, also exploiting a common sense ontology. The service is accessible using a multimodal browser on Personal Digital Assistants (PDAs); the browser allows the user to interact with the…

Editorial: Robot-Assisted Learning and Education

Interaction Capabilities of a Robotic Receptionist

A system aimed at facilitating the interaction between a human user and an humanoid robot is presented. The system is suited to answer questions about laboratories activities, people involved, projects, research themes and collaborations among employees. The task is accomplished by the HermiT reasoner invoked by a speech recognition module. The system is capable of navigating a specific ontology making inference on it. The presented system is part of a broader social robot framework whose goal is to give the user a fulfilling social interaction experience, driven by the perception of the robot internal state and involving intuitive and computational creativity capabilities.

A Knowledge Management and Decision Support Model for Enterprises

We propose a novel knowledge management system (KMS) for enterprises. Our system exploits two different approaches for knowledge representation and reasoning: a document-based approach based on data-driven creation of a semantic space and an ontology-based model. Furthermore, we provide an expert system capable of supporting the enterprise decisional processes and a semantic engine which performs intelligent search on the enterprise knowledge bases. The decision support process exploits the Bayesian networks model to improve business planning process when performed under uncertainty. Copyright © 2011 Patrizia Ribino et al.

A Virtual Shopper Customer Assistant in Pervasive Environments

In this work we propose a smart, human-like PDA-based personal shopper assistant. The system is able to understand the user needs through a spoken natural language interaction and then stores the preferences of the potential customer. Subsequently the personal shopper suggests the most suitable items and shops that match the user profile. The interaction is given by automatic speech recognition and text-to-speech technologies; localization is allowed by the use of Wireless technologies, while the interaction is performed by an Alice-based chat-bot endowed with reasoning capabilities. Besides, being implemented on a PDA, the personal shopper satisfies the user needs of mobility and it is als…

LSA-Enhanced Ontologies for Information Exploration System on Cultural Heritage

A Study on Classification Methods Applied to Sentiment Analysis

Sentiment analysis is a new area of research in data mining that concerns the detection of opinions and/or sentiments in texts. This work focuses on the application and the comparison of three classification techniques over a text corpus composed of reviews of commercial products in order to detect opinions about them. The chosen domain is about "perfumes", and user opinions composing the corpus are written in Italian language. The proposed approach is completely data-driven: a Term Frequency / Inverse Document Frequency (TFIDF) terms selection procedure has been applied in order to make computation more efficient, to improve the classification results and to manage some issues related to t…

LSA for Intuitive Chat-Agents Tutoring System

An ACT-R Based Humanoid Social Robot to Manage Storytelling Activities

This paper describes an interactive storytelling system, accessible through the SoftBank robotic platforms NAO and Pepper. The main contribution consists of the interpretation of the story characters by humanoid robots, obtained through the definition of appropriate cognitive models, relying on the ACT-R cognitive architecture. The reasoning processes leading to the story evolution are based on the represented knowledge and the suggestions of the listener in critical points of the story. They are disclosed during the narration, to make clear the dynamics of the story and the feelings of the characters. We analyzed the impact of such externalization of the internal status of the characters t…

A Virtual Shopper Customer Assistant in Pervasive Environments.

A Conversational Agent Based on a Conceptual Interpretation of a Data Driven Semantic Space

In this work we propose an interpretation of the LSA framework which leads to a data-driven “conceptual” space creation suitable for an “intuitive” conversational agent. The proposed approach allows overcoming the limitations of traditional, rule-based, chat-bots, leading to a more natural dialogue.

EHeBby: An evocative humorist chat-bot

A conversational agent, capable to have a "sense of humor" is presented. The agent can both generate humorous sentences and recognize humoristic expressions introduced by the user during the dialogue. EHeBby is an entertainment oriented conversational agent implemented using the ALICE framework embedded into an Yahoo! Messenger client. It is characterized by two areas: a rational, rule-based area and an evocative area. The first one is based on well founded techniques of computational humor and a standard AIML KB. The second one is based on a conceptual space, automatically induced by a corpus of funny documents, where KB items and user sentences are mapped. This area emulates an associativ…

An Innovative Similarity Measure for Sentence Plagiarism Detection

We propose and experimentally assess Semantic Word Error Rate (SWER), an innovative similarity measure for sentence plagiarism detection. SWER introduces a complex approach based on latent semantic analysis, which is capable of outperforming the accuracy of competitor methods in plagiarism detection. We provide principles and functionalities of SWER, and we complement our analytical contribution by means of a significant preliminary experimental analysis. Derived results are promising, and confirm to use the goodness of our proposal.

Jade and Aiml: A Multi-Agents Tutoring System

Convergence of Web 2.0 and Semantic Web: A Semantic Tagging and Searching System for Creating and Searching Blogs

The work presented in this paper aims to combine Latent Semantic Analysis methodology, common sense and traditional knowledge representation in order to improve the dialogue capabilities of a conversational agent. In our approach the agent brain is characterized by two areas: a "rational area", composed by a structured, rule-based knowledge base, and an "associative area", obtained through a data- driven semantic space. Concepts are mapped in this space and their mutual geometric distance is related to their conceptual similarity. The geometric distance between concepts implicitly defines a sub-symbolic relationship net, which can be seen as a new "sub- symbolic semantic layer" automaticall…