Andrea Ciapetti - Academia.edu (original) (raw)

Book & Paper Reviews by Andrea Ciapetti

Research paper thumbnail of ARCHEOFOSS Open Source, Free Software e Open Format nei processi di ricerca archeologica Atti del VI Workshop (Napoli, 9-10 giugno 2011) a cura di Francesca Cantone

by Francesca Cantone, Alessandro Bezzi, Alessio Paonessa, Piro Fabio, luca bianconi, Pietro Citarella, Progetto SITAR, Andrea Ciapetti, Luca d'Altilia, Davide Debernardi, and Davide Merlitti

ARCHEOFOSS Open Source, Free Software e Open Format nei processi di ricerca archeologica. Atti de... more ARCHEOFOSS
Open Source, Free Software e Open Format nei processi di ricerca archeologica. Atti del VI Workshop (Napoli, 9-10 giugno 2011)

Papers by Andrea Ciapetti

Research paper thumbnail of Action Recognition in Surveillance Videos Using Semantic Web Rules

In this paper an approach to detect high level events using Semantic Web Rules (SWRL), will be pr... more In this paper an approach to detect high level events using Semantic Web Rules (SWRL), will be presented. This approach combines middle-level events and information about actors and actions, extracted from a Visual Analysis module, with a semantic rules inference system to detect meaningful high level crime scenarios. The middle-level events and the spatial and temporal information is indexed in an optimized semantic data-store, where rules for detecting events are manually defined using SWRL. When these rules are applied to the indexed information, high level events can be detected. Early tests of the system successfully detect fights, pickpocketing, thefts and more general “suspicious events”. The work needed to perform this process in CCTV videos in an automated and unattended fashion has been challenging in terms of aggregation of data and optimisation of the different subsystems involved in the process. Specially to make results available in a reasonable time to apply these techniques in a production environment in police stations.

Research paper thumbnail of NETHIC: A System for Automatic Text Classification using Neural Networks and Hierarchical Taxonomies

Research paper thumbnail of A Semantic Knowledge Discovery Framework for Detecting Online Terrorist Networks

Lecture Notes in Computer Science, Dec 11, 2018

This paper presents a knowledge discovery framework, with the purpose of detecting terrorist pres... more This paper presents a knowledge discovery framework, with the purpose of detecting terrorist presence in terms of potential suspects and networks on the open and Deep Web. The framework combines information extraction methods and tools and natural language processing techniques, together with semantic information derived from social network analysis, in order to automatically process online content coming from disparate sources and identify people and relationships that may be linked to terrorist activities. This framework has been developed within the context of the DANTE Horizon 2020 project, as part of a larger international effort to detect and analyze terrorist-related content from online sources and help international police organizations in their investigations against crime and terrorism.

Research paper thumbnail of An Automatic Text Classification Method Based on Hierarchical Taxonomies, Neural Networks and Document Embedding: The NETHIC Tool

Lecture notes in business information processing, 2020

This work describes an automatic text classification method implemented in a software tool called... more This work describes an automatic text classification method implemented in a software tool called NETHIC, which takes advantage of the inner capabilities of highly-scalable neural networks combined with the expressiveness of hierarchical taxonomies. As such, NETHIC succeeds in bringing about a mechanism for text classification that proves to be significantly effective as well as efficient. The tool had undergone an experimentation process against both a generic and a domain-specific corpus, outputting promising results. On the basis of this experimentation, NETHIC has been now further refined and extended by adding a document embedding mechanism, which has shown improvements in terms of performance on the individual networks and on the whole hierarchical model.

Research paper thumbnail of An Automatic Text Classification Method Based on Hierarchical Taxonomies, Neural Networks and Document Embedding: The NETHIC Tool

Enterprise Information Systems, 2020

This work describes an automatic text classification method implemented in a software tool called... more This work describes an automatic text classification method implemented in a software tool called NETHIC, which takes advantage of the inner capabilities of highly-scalable neural networks combined with the expressiveness of hierarchical taxonomies. As such, NETHIC succeeds in bringing about a mechanism for text classification that proves to be significantly effective as well as efficient. The tool had undergone an experimentation process against both a generic and a domain-specific corpus, outputting promising results. On the basis of this experimentation, NETHIC has been now further refined and extended by adding a document embedding mechanism, which has shown improvements in terms of performance on the individual networks and on the whole hierarchical model.

Research paper thumbnail of ARCHEOFOSS OPEN SOURCE, FREE SOFTWARE E OPEN FORMAT NEI PROCESSI DI RICERCA ARCHEOLOGICA. Atti del IV Workshop (Roma, 27-28 aprile 2009)

established by: Mauro Cristofani and Riccardo Francovich, 2009

... Title, ARCHEOFOSS OPEN SOURCE, FREE SOFTWARE E OPEN FORMAT NEI PROCESSI DI RICERCA ARCHEOLOGI... more ... Title, ARCHEOFOSS OPEN SOURCE, FREE SOFTWARE E OPEN FORMAT NEI PROCESSI DI RICERCA ARCHEOLOGICA. ... Rif. Cignoni P., Palombini S., Pescarin S. (eds.) ARCHEOFOSS Open Source, Free Software e Open Format nei processi di ricerca archeologica. ...

Research paper thumbnail of Enabling Enterprise Semantic Search through Language Technologies: the ProgressIt Experience

Italian Information Retrieval Workshop, 2014

Research paper thumbnail of Enabling Enterprise Semantic Search through Language Technologies: the ProgressIt Experience

Abstract. This paper presents the platform targeted in the PROGRESS-IT project. It represents an ... more Abstract. This paper presents the platform targeted in the PROGRESS-IT project. It represents an Enterprise Semantic Search engine tailored for Small and Medium Sized Enterprises to retrieve information about Projects, Grants, Patents or Scientific Papers. The proposed solution improves the usability and quality of standard search engines through Distributional models of Lexical Semantics. The quality of the Keyword Search has been improved with Query Suggestion, Expansion and Result Re-Ranking. Moreover, the interaction with the system has been specialized for the analysts by defining a set of Dashboards designed to enable richer queries avoiding the complexity of their definition. This paper shows the application of Linguistic Technologies, such as the Structured Semantic Similarity function to measure the relatedness between documents. These are then used in the retrieval process, for example to ask the system for Project Ideas directly using an Organization Description as a quer...

Research paper thumbnail of NETHIC: A System for Automatic Text Classification using Neural Networks and Hierarchical Taxonomies

This paper presents NETHIC, a software system for the automatic classification of textual documen... more This paper presents NETHIC, a software system for the automatic classification of textual documents based on hierarchical taxonomies and artificial neural networks. This approach combines the advantages of highlystructured hierarchies of textual labels with the versatility and scalability of neural networks, thus bringing about a textual classifier that displays high levels of performance in terms of both effectiveness and efficiency. The system has first been tested as a general-purpose classifier on a generic document corpus, and then applied to the specific domain tackled by DANTE, a European project that is meant to address criminal and terroristrelated online contents, showing consistent results across both application domains.

Research paper thumbnail of Enabling Enterprise Semantic Search through Language Technologies: the ProgressIt Experience

This paper presents the platform targeted in the PROGRESS-IT project. It represents an Enterprise... more This paper presents the platform targeted in the PROGRESS-IT project. It represents an Enterprise Semantic Search engine tailored for Small and Medium Sized Enterprises to retrieve information about Projects, Grants, Patents or Scientific Papers. The proposed solution improves the usability and quality of standard search engines through Distributional models of Lexical Semantics. The quality of the Keyword Search has been improved with Query Suggestion, Expansion and Result Re-Ranking. Moreover, the interaction with the system has been specialized for the analysts by defining a set of Dashboards designed to enable richer queries avoiding the complexity of their definition. This paper shows the application of Linguistic Technologies, such as the Structured Semantic Similarity function to measure the relatedness between documents. These are then used in the retrieval process, for example to ask the system for Project Ideas directly using an Organization Description as a query. The res...

Research paper thumbnail of A Semantic Knowledge Discovery Framework for Detecting Online Terrorist Networks

This paper presents a knowledge discovery framework, with the purpose of detecting terrorist pres... more This paper presents a knowledge discovery framework, with the purpose of detecting terrorist presence in terms of potential suspects and networks on the open and Deep Web. The framework combines information extraction methods and tools and natural language processing techniques, together with semantic information derived from social network analysis, in order to automatically process online content coming from disparate sources and identify people and relationships that may be linked to terrorist activities. This framework has been developed within the context of the DANTE Horizon 2020 project, as part of a larger international effort to detect and analyze terrorist-related content from online sources and help international police organizations in their investigations against crime and terrorism.

Research paper thumbnail of SURVANT: An Innovative Semantics-Based Surveillance Video Archives Investigation Assistant

Research paper thumbnail of An Automatic Text Classification Method Based on Hierarchical Taxonomies, Neural Networks and Document Embedding: The NETHIC Tool

This work describes an automatic text classification method implemented in a software tool called... more This work describes an automatic text classification method implemented in a software tool called NETHIC, which takes advantage of the inner capabilities of highly-scalable neural networks combined with the expressiveness of hierarchical taxonomies. As such, NETHIC succeeds in bringing about a mechanism for text classification that proves to be significantly effective as well as efficient. The tool had undergone an experimentation process against both a generic and a domain-specific corpus, outputting promising results. On the basis of this experimentation, NETHIC has been now further refined and extended by adding a document embedding mechanism, which has shown improvements in terms of performance on the individual networks and on the whole hierarchical model.

Research paper thumbnail of SKOSifying User Generated Content

The increasing social approach to information sharing causes expectations of growth of the inform... more The increasing social approach to information sharing causes expectations of growth of the information assets and stimulates contributions to the creation of new information and knowledge. User Generated Content (UGC) is lacking a uniform and agreed structure and tagging system (metadata), which makes uneasy to share knowledge on the web. The challenge is to combine the advantages and flexibility of Web 2.0 and folksonomies with a rigorous approach inherent to Semantic Web and ontologies. The LABC (LABoratories for Culture) project is aimed to develop an innovative multimedia web 3.0 platform which enables capturing, sharing, and enjoying data on tangible and intangible cultural and environmental heritage. The platform is designed to collect resources from a broad community of users, and to reformulate such contents into scientifically structured information using Semantic Web tools and technologies. The platform allows for the creation of various specialized environments (Laborator...

Research paper thumbnail of SKOSifying User Generated Content

The increasing social approach to information sharing causes expectations of growth of the inform... more The increasing social approach to information sharing causes expectations of growth of the information assets and stimulates contributions to the creation of new information and knowledge. User Generated Content (UGC) is lacking a uniform and agreed structure and tagging system (metadata), which makes uneasy to share knowledge on the web. The challenge is to combine the advantages and flexibility of Web 2.0 and folksonomies with a rigorous approach inherent to Semantic Web and ontologies. The LABC (LABoratories for Culture) project is aimed to develop an innovative multimedia web 3.0 platform which enables capturing, sharing, and enjoying data on tangible and intangible cultural and environmental heritage. The platform is designed to collect resources from a broad community of users, and to reformulate such contents into scientifically structured information using Semantic Web tools and technologies. The platform allows for the creation of various specialized environments (Laborator...

Research paper thumbnail of SKOSifying User Generated Content

The increasing social approach to information sharing causes expectations of growth of the inform... more The increasing social approach to information sharing causes expectations of growth of the information assets and stimulates contributions to the creation of new information and knowledge. User Generated Content (UGC) is lacking a uniform and agreed structure and tagging system (metadata), which makes uneasy to share knowledge on the web. The challenge is to combine the advantages and flexibility of Web 2.0 and folksonomies with a rigorous approach inherent to Semantic Web and ontologies. The LABC (LABoratories for Culture) project is aimed to develop an innovative multimedia web 3.0 platform which enables capturing, sharing, and enjoying data on tangible and intangible cultural and environmental heritage. The platform is designed to collect resources from a broad community of users, and to reformulate such contents into scientifically structured information using Semantic Web tools and technologies. The platform allows for the creation of various specialized environments (Laborator...

Research paper thumbnail of ARCHEOFOSS Open Source, Free Software e Open Format nei processi di ricerca archeologica Atti del VI Workshop (Napoli, 9-10 giugno 2011) a cura di Francesca Cantone

by Francesca Cantone, Alessandro Bezzi, Alessio Paonessa, Piro Fabio, luca bianconi, Pietro Citarella, Progetto SITAR, Andrea Ciapetti, Luca d'Altilia, Davide Debernardi, and Davide Merlitti

ARCHEOFOSS Open Source, Free Software e Open Format nei processi di ricerca archeologica. Atti de... more ARCHEOFOSS
Open Source, Free Software e Open Format nei processi di ricerca archeologica. Atti del VI Workshop (Napoli, 9-10 giugno 2011)

Research paper thumbnail of Action Recognition in Surveillance Videos Using Semantic Web Rules

In this paper an approach to detect high level events using Semantic Web Rules (SWRL), will be pr... more In this paper an approach to detect high level events using Semantic Web Rules (SWRL), will be presented. This approach combines middle-level events and information about actors and actions, extracted from a Visual Analysis module, with a semantic rules inference system to detect meaningful high level crime scenarios. The middle-level events and the spatial and temporal information is indexed in an optimized semantic data-store, where rules for detecting events are manually defined using SWRL. When these rules are applied to the indexed information, high level events can be detected. Early tests of the system successfully detect fights, pickpocketing, thefts and more general “suspicious events”. The work needed to perform this process in CCTV videos in an automated and unattended fashion has been challenging in terms of aggregation of data and optimisation of the different subsystems involved in the process. Specially to make results available in a reasonable time to apply these techniques in a production environment in police stations.

Research paper thumbnail of NETHIC: A System for Automatic Text Classification using Neural Networks and Hierarchical Taxonomies

Research paper thumbnail of A Semantic Knowledge Discovery Framework for Detecting Online Terrorist Networks

Lecture Notes in Computer Science, Dec 11, 2018

This paper presents a knowledge discovery framework, with the purpose of detecting terrorist pres... more This paper presents a knowledge discovery framework, with the purpose of detecting terrorist presence in terms of potential suspects and networks on the open and Deep Web. The framework combines information extraction methods and tools and natural language processing techniques, together with semantic information derived from social network analysis, in order to automatically process online content coming from disparate sources and identify people and relationships that may be linked to terrorist activities. This framework has been developed within the context of the DANTE Horizon 2020 project, as part of a larger international effort to detect and analyze terrorist-related content from online sources and help international police organizations in their investigations against crime and terrorism.

Research paper thumbnail of An Automatic Text Classification Method Based on Hierarchical Taxonomies, Neural Networks and Document Embedding: The NETHIC Tool

Lecture notes in business information processing, 2020

This work describes an automatic text classification method implemented in a software tool called... more This work describes an automatic text classification method implemented in a software tool called NETHIC, which takes advantage of the inner capabilities of highly-scalable neural networks combined with the expressiveness of hierarchical taxonomies. As such, NETHIC succeeds in bringing about a mechanism for text classification that proves to be significantly effective as well as efficient. The tool had undergone an experimentation process against both a generic and a domain-specific corpus, outputting promising results. On the basis of this experimentation, NETHIC has been now further refined and extended by adding a document embedding mechanism, which has shown improvements in terms of performance on the individual networks and on the whole hierarchical model.

Research paper thumbnail of An Automatic Text Classification Method Based on Hierarchical Taxonomies, Neural Networks and Document Embedding: The NETHIC Tool

Enterprise Information Systems, 2020

This work describes an automatic text classification method implemented in a software tool called... more This work describes an automatic text classification method implemented in a software tool called NETHIC, which takes advantage of the inner capabilities of highly-scalable neural networks combined with the expressiveness of hierarchical taxonomies. As such, NETHIC succeeds in bringing about a mechanism for text classification that proves to be significantly effective as well as efficient. The tool had undergone an experimentation process against both a generic and a domain-specific corpus, outputting promising results. On the basis of this experimentation, NETHIC has been now further refined and extended by adding a document embedding mechanism, which has shown improvements in terms of performance on the individual networks and on the whole hierarchical model.

Research paper thumbnail of ARCHEOFOSS OPEN SOURCE, FREE SOFTWARE E OPEN FORMAT NEI PROCESSI DI RICERCA ARCHEOLOGICA. Atti del IV Workshop (Roma, 27-28 aprile 2009)

established by: Mauro Cristofani and Riccardo Francovich, 2009

... Title, ARCHEOFOSS OPEN SOURCE, FREE SOFTWARE E OPEN FORMAT NEI PROCESSI DI RICERCA ARCHEOLOGI... more ... Title, ARCHEOFOSS OPEN SOURCE, FREE SOFTWARE E OPEN FORMAT NEI PROCESSI DI RICERCA ARCHEOLOGICA. ... Rif. Cignoni P., Palombini S., Pescarin S. (eds.) ARCHEOFOSS Open Source, Free Software e Open Format nei processi di ricerca archeologica. ...

Research paper thumbnail of Enabling Enterprise Semantic Search through Language Technologies: the ProgressIt Experience

Italian Information Retrieval Workshop, 2014

Research paper thumbnail of Enabling Enterprise Semantic Search through Language Technologies: the ProgressIt Experience

Abstract. This paper presents the platform targeted in the PROGRESS-IT project. It represents an ... more Abstract. This paper presents the platform targeted in the PROGRESS-IT project. It represents an Enterprise Semantic Search engine tailored for Small and Medium Sized Enterprises to retrieve information about Projects, Grants, Patents or Scientific Papers. The proposed solution improves the usability and quality of standard search engines through Distributional models of Lexical Semantics. The quality of the Keyword Search has been improved with Query Suggestion, Expansion and Result Re-Ranking. Moreover, the interaction with the system has been specialized for the analysts by defining a set of Dashboards designed to enable richer queries avoiding the complexity of their definition. This paper shows the application of Linguistic Technologies, such as the Structured Semantic Similarity function to measure the relatedness between documents. These are then used in the retrieval process, for example to ask the system for Project Ideas directly using an Organization Description as a quer...

Research paper thumbnail of NETHIC: A System for Automatic Text Classification using Neural Networks and Hierarchical Taxonomies

This paper presents NETHIC, a software system for the automatic classification of textual documen... more This paper presents NETHIC, a software system for the automatic classification of textual documents based on hierarchical taxonomies and artificial neural networks. This approach combines the advantages of highlystructured hierarchies of textual labels with the versatility and scalability of neural networks, thus bringing about a textual classifier that displays high levels of performance in terms of both effectiveness and efficiency. The system has first been tested as a general-purpose classifier on a generic document corpus, and then applied to the specific domain tackled by DANTE, a European project that is meant to address criminal and terroristrelated online contents, showing consistent results across both application domains.

Research paper thumbnail of Enabling Enterprise Semantic Search through Language Technologies: the ProgressIt Experience

This paper presents the platform targeted in the PROGRESS-IT project. It represents an Enterprise... more This paper presents the platform targeted in the PROGRESS-IT project. It represents an Enterprise Semantic Search engine tailored for Small and Medium Sized Enterprises to retrieve information about Projects, Grants, Patents or Scientific Papers. The proposed solution improves the usability and quality of standard search engines through Distributional models of Lexical Semantics. The quality of the Keyword Search has been improved with Query Suggestion, Expansion and Result Re-Ranking. Moreover, the interaction with the system has been specialized for the analysts by defining a set of Dashboards designed to enable richer queries avoiding the complexity of their definition. This paper shows the application of Linguistic Technologies, such as the Structured Semantic Similarity function to measure the relatedness between documents. These are then used in the retrieval process, for example to ask the system for Project Ideas directly using an Organization Description as a query. The res...

Research paper thumbnail of A Semantic Knowledge Discovery Framework for Detecting Online Terrorist Networks

This paper presents a knowledge discovery framework, with the purpose of detecting terrorist pres... more This paper presents a knowledge discovery framework, with the purpose of detecting terrorist presence in terms of potential suspects and networks on the open and Deep Web. The framework combines information extraction methods and tools and natural language processing techniques, together with semantic information derived from social network analysis, in order to automatically process online content coming from disparate sources and identify people and relationships that may be linked to terrorist activities. This framework has been developed within the context of the DANTE Horizon 2020 project, as part of a larger international effort to detect and analyze terrorist-related content from online sources and help international police organizations in their investigations against crime and terrorism.

Research paper thumbnail of SURVANT: An Innovative Semantics-Based Surveillance Video Archives Investigation Assistant

Research paper thumbnail of An Automatic Text Classification Method Based on Hierarchical Taxonomies, Neural Networks and Document Embedding: The NETHIC Tool

This work describes an automatic text classification method implemented in a software tool called... more This work describes an automatic text classification method implemented in a software tool called NETHIC, which takes advantage of the inner capabilities of highly-scalable neural networks combined with the expressiveness of hierarchical taxonomies. As such, NETHIC succeeds in bringing about a mechanism for text classification that proves to be significantly effective as well as efficient. The tool had undergone an experimentation process against both a generic and a domain-specific corpus, outputting promising results. On the basis of this experimentation, NETHIC has been now further refined and extended by adding a document embedding mechanism, which has shown improvements in terms of performance on the individual networks and on the whole hierarchical model.

Research paper thumbnail of SKOSifying User Generated Content

The increasing social approach to information sharing causes expectations of growth of the inform... more The increasing social approach to information sharing causes expectations of growth of the information assets and stimulates contributions to the creation of new information and knowledge. User Generated Content (UGC) is lacking a uniform and agreed structure and tagging system (metadata), which makes uneasy to share knowledge on the web. The challenge is to combine the advantages and flexibility of Web 2.0 and folksonomies with a rigorous approach inherent to Semantic Web and ontologies. The LABC (LABoratories for Culture) project is aimed to develop an innovative multimedia web 3.0 platform which enables capturing, sharing, and enjoying data on tangible and intangible cultural and environmental heritage. The platform is designed to collect resources from a broad community of users, and to reformulate such contents into scientifically structured information using Semantic Web tools and technologies. The platform allows for the creation of various specialized environments (Laborator...

Research paper thumbnail of SKOSifying User Generated Content

The increasing social approach to information sharing causes expectations of growth of the inform... more The increasing social approach to information sharing causes expectations of growth of the information assets and stimulates contributions to the creation of new information and knowledge. User Generated Content (UGC) is lacking a uniform and agreed structure and tagging system (metadata), which makes uneasy to share knowledge on the web. The challenge is to combine the advantages and flexibility of Web 2.0 and folksonomies with a rigorous approach inherent to Semantic Web and ontologies. The LABC (LABoratories for Culture) project is aimed to develop an innovative multimedia web 3.0 platform which enables capturing, sharing, and enjoying data on tangible and intangible cultural and environmental heritage. The platform is designed to collect resources from a broad community of users, and to reformulate such contents into scientifically structured information using Semantic Web tools and technologies. The platform allows for the creation of various specialized environments (Laborator...

Research paper thumbnail of SKOSifying User Generated Content

The increasing social approach to information sharing causes expectations of growth of the inform... more The increasing social approach to information sharing causes expectations of growth of the information assets and stimulates contributions to the creation of new information and knowledge. User Generated Content (UGC) is lacking a uniform and agreed structure and tagging system (metadata), which makes uneasy to share knowledge on the web. The challenge is to combine the advantages and flexibility of Web 2.0 and folksonomies with a rigorous approach inherent to Semantic Web and ontologies. The LABC (LABoratories for Culture) project is aimed to develop an innovative multimedia web 3.0 platform which enables capturing, sharing, and enjoying data on tangible and intangible cultural and environmental heritage. The platform is designed to collect resources from a broad community of users, and to reformulate such contents into scientifically structured information using Semantic Web tools and technologies. The platform allows for the creation of various specialized environments (Laborator...