Studying, understanding and exploiting the content of a document collection require automatic tec... more Studying, understanding and exploiting the content of a document collection require automatic techniques that can effectively support the users in extracting useful information from it and reason with this information. Concept networks (e.g., taxonomies) may play a relevant role in this perspective, but are seldom available, and cannot be manually built and maintained cheaply and reliably. On the other hand, automated learning of these resources from text needs to be robust with respect to missing or partial knowledge, because often only sparse fragments of the target network can be extracted. This work presents ConNeKTion, a tool that is able to learn concept networks from plain text and to structure and enrich them by finding concept generalizations. The proposed methodologies are general and applicable to any language. It also provides functionalities for the exploitation of the learned knowledge, and a control panel that allows the user to comfortably carry out these activities. Several experiments and applications are reported, showing the usefulness and flexibility of ConNeKTion.
Analogy is the cognitive process of matching the characterizing features of two different items. ... more Analogy is the cognitive process of matching the characterizing features of two different items. This may enable reuse of knowledge across domains , which can help to solve problems. Indeed, abstracting the 'role' of the features away from their specific embodiment in the single items is fundamental to recognize the possibility of an analogical mapping between them. The analogical reasoning process consists of five steps: retrieval, mapping, evaluation , abstraction and re-representation. This paper proposes two forms of an operator that includes all these elements, providing more power and flexibility than existing systems. In particular, the Roles Mapper leverages the presence of identical descriptors in the two domains, while the Roles Argumentation-based Mapper removes also this limitation. For generality and compliance with other reasoning operators in a multi-strategy inference setting, they exploit a simple formalism based on First-Order Logic and do not require any background knowledge or meta-knowledge. Applied to the most critical classical examples in the literature, they proved to be able to find insightful analogies.
Conversational agents have been widely used in pedagogical contexts. They have the advantage of o... more Conversational agents have been widely used in pedagogical contexts. They have the advantage of offering to users not only a task-oriented support, but also the possibility to relate with the system at social level. Therefore, besides endowing the conversational agent with knowledge necessary to fulfill pedagogical goals, it is important to provide the agent with social intelligence. To do so the agent should be able to recognize the social attitude of the user during the interaction in order to accommodate the conversational strategy. In this paper we illustrate how we defined and applied a model for recognizing the social attitude of the student in natural interaction with a Pedagogical Conversational Agent (PCA) starting from the linguistic, acoustic and gestural analysis of the communicative act.
Traffic Mining Applied to Police Activities (AISC series, Springer), 2018
The research on traffic flows is historically born to improve road networks, to make trips comfor... more The research on traffic flows is historically born to improve road networks, to make trips comfortable and faster. In this research field, as in many others, literary production followed market or business demand. This paper has the objective to clarify police needs, in order to create a research request and to gain attention. It provides an organizational framework concerning needs, goals, fields and some impacts such that different areas of study can concur all together towards a pervasive comprehension of road events, a predictive Traffic Police, so that safety and security can be ensured via a targeted patrolling or intervention. The aim behind the practical level is to pave the way for the interaction between data science from one hand, and law, public administration and justice from the other hand.
Studying, understanding and exploiting the content of a document collection require automatic tec... more Studying, understanding and exploiting the content of a document collection require automatic techniques that can effectively support the users in extracting useful information from it and reason with this information. Concept networks (e.g., taxonomies) may play a relevant role in this perspective, but are seldom available, and cannot be manually built and maintained cheaply and reliably. On the other hand, automated learning of these resources from text needs to be robust with respect to missing or partial knowledge, because often only sparse fragments of the target network can be extracted. This work presents ConNeKTion, a tool that is able to learn concept networks from plain text and to structure and enrich them by finding concept generalizations. The proposed methodologies are general and applicable to any language. It also provides functionalities for the exploitation of the learned knowledge, and a control panel that allows the user to comfortably carry out these activities. Several experiments and applications are reported, showing the usefulness and flexibility of ConNeKTion.
Analogy is the cognitive process of matching the characterizing features of two different items. ... more Analogy is the cognitive process of matching the characterizing features of two different items. This may enable reuse of knowledge across domains , which can help to solve problems. Indeed, abstracting the 'role' of the features away from their specific embodiment in the single items is fundamental to recognize the possibility of an analogical mapping between them. The analogical reasoning process consists of five steps: retrieval, mapping, evaluation , abstraction and re-representation. This paper proposes two forms of an operator that includes all these elements, providing more power and flexibility than existing systems. In particular, the Roles Mapper leverages the presence of identical descriptors in the two domains, while the Roles Argumentation-based Mapper removes also this limitation. For generality and compliance with other reasoning operators in a multi-strategy inference setting, they exploit a simple formalism based on First-Order Logic and do not require any background knowledge or meta-knowledge. Applied to the most critical classical examples in the literature, they proved to be able to find insightful analogies.
Conversational agents have been widely used in pedagogical contexts. They have the advantage of o... more Conversational agents have been widely used in pedagogical contexts. They have the advantage of offering to users not only a task-oriented support, but also the possibility to relate with the system at social level. Therefore, besides endowing the conversational agent with knowledge necessary to fulfill pedagogical goals, it is important to provide the agent with social intelligence. To do so the agent should be able to recognize the social attitude of the user during the interaction in order to accommodate the conversational strategy. In this paper we illustrate how we defined and applied a model for recognizing the social attitude of the student in natural interaction with a Pedagogical Conversational Agent (PCA) starting from the linguistic, acoustic and gestural analysis of the communicative act.
Traffic Mining Applied to Police Activities (AISC series, Springer), 2018
The research on traffic flows is historically born to improve road networks, to make trips comfor... more The research on traffic flows is historically born to improve road networks, to make trips comfortable and faster. In this research field, as in many others, literary production followed market or business demand. This paper has the objective to clarify police needs, in order to create a research request and to gain attention. It provides an organizational framework concerning needs, goals, fields and some impacts such that different areas of study can concur all together towards a pervasive comprehension of road events, a predictive Traffic Police, so that safety and security can be ensured via a targeted patrolling or intervention. The aim behind the practical level is to pave the way for the interaction between data science from one hand, and law, public administration and justice from the other hand.
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Papers by Fabio Leuzzi