Giovanni Semeraro – författare

This monograph gives a complete overview of the techniques and the methods for semantics-aware content representation and shows how to apply such techniques in various use cases, such as recommender systems, user profiling and social media analysis.Throughout the book, the authors provide an extensive analysis of the techniques currently proposed in the literature and cover all the available tools and libraries to implement and exploit such methodologies in real-world scenarios.The book first introduces the problem of information overload and the reasons why content-based information needs to be taken into account. Next, the basics of Natural Language Processing are provided, by describing operations such as tokenization, stopword removal, lemmatization, stemming, part-of-speech tagging, along with the main problems and issues. Finally, the book describes the different approaches for semantics-aware content representation: such approaches are split into ‘exogenous’ and ‘endogenous’ ones, depending on whether external knowledge sources as DBpedia or geometrical models and distributional semantics are used, respectively. To conclude, several successful use cases and an extensive list of available tools and resources to implement the approaches are shown.Semantics in Adaptive and Personalised Systems definitely fills the gap between the extensive literature on content-based recommender systems, natural language processing, and the different types of semantics-aware representations.

This book focuses on new research challenges in intelligent information filtering and retrieval. It collects invited chapters and extended research contributions from DART 2014 (the 8th International Workshop on Information Filtering and Retrieval), held in Pisa (Italy), on December 10, 2014, and co-hosted with the XIII AI*IA Symposium on Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world contexts. The chapters of this book present a comprehensive review of related works and the current state of the art. The contributions from both practitioners and researchers have been carefully reviewed by experts in the area, who also gave useful suggestions to improve the quality of the book.

This book addresses new challenges and emerging ideas in Distributed Information Filtering and Retrieval. It gathers extended papers presented at DART 2013 (the 7th International Workshop on Information Filtering and Retrieval), held on December 6, 2013 in Turin, Italy, and co-hosted with the XIII International Conference of the Italian Association for Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world contexts. The papers presented here offer a comprehensive review of related work and state-of-the-art techniques. The authors – a mix of respected practitioners and researchers – share their findings on a range of topics, including data leak protection on text comparison, natural language processing, ambient intelligence, information retrieval and web portals, and knowledge management. All contributions were carefully reviewed by experts in the respective area, who also provided useful suggestions to improve the book’s overall quality.

This book focuses on new research challenges in intelligent information filtering and retrieval.

This book addresses new challenges and emerging ideas in Distributed Information Filtering and Retrieval. It gathers extended papers presented at DART 2013 (the 7th International Workshop on Information Filtering and Retrieval), held on December 6, 2013 in Turin, Italy, and co-hosted with the XIII International Conference of the Italian Association for Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world contexts. The papers presented here offer a comprehensive review of related work and state-of-the-art techniques. The authors – a mix of respected practitioners and researchers – share their findings on a range of topics, including data leak protection on text comparison, natural language processing, ambient intelligence, information retrieval and web portals, and knowledge management. All contributions were carefully reviewed by experts in the respective area, who also provided useful suggestions to improve the book’s overall quality.

This book constitutes the refereed proceedings of the 16th International Symposium on Methodologies for Intelligent Systems, ISMIS 2006. The book presents 81 revised papers together with 3 invited papers. Topical sections include active media human-computer interaction, computational intelligence, intelligent agent technology, intelligent information retrieval, intelligent information systems, knowledge representation and integration, knowledge discovery and data mining, logic for AI and logic programming, machine learning, text mining, and Web intelligence.

Finding knowledge – or meaning – in data is the goal of every knowledge d- covery e?ort. Subsequent goals and questions regarding this knowledge di?er amongknowledgediscovery(KD) projectsandapproaches. Onecentralquestion is whether and to what extent the meaning extracted from the data is expressed in a formal way that allows not only humans but also machines to understand and re-use it, i. e. , whether the semantics are formal semantics. Conversely, the input to KD processes di?ers between KD projects and approaches. One central questioniswhetherthebackgroundknowledge,businessunderstanding,etc. that the analyst employs to improve the results of KD is a set of natural-language statements, a theory in a formal language, or somewhere in between. Also, the data that are being mined can be more or less structured and/or accompanied by formal semantics. These questions must be asked in every KD e?ort. Nowhere may they be more pertinent, however, than in KD from Web data (“Web mining”). Thisis due especially to the vast amounts and heterogeneity of data and ba- ground knowledge available for Web mining (content, link structure, and - age), and to the re-use of background knowledge and KD results over the Web as a global knowledge repository and activity space. In addition, the (Sem- tic) Web can serve as a publishing space for the results of knowledge discovery from other resources, especially if the whole process is underpinned by common ontologies.

The World Wide Web is a rich source of information about human behavior. It containslarge amount of data organizedvia interconnected Web pages,traces of information search, user feedback on items of interest, etc. In addition to large data volumes, one of the important characteristics of the Web is its dynamics, where content,structure and usagearechanging over time. This showsup in the rise of related research areas like communities of practice, knowledge mana- ment, Web communities, and peer-to-peer. In particular the notion of colla- rative work and thus the need of its systematic analysis become more and more important. For instance, to develop e?ective Web applications, it is essential to analyze patterns hidden in the usage of Web resources, their contents and their interconnections. Machine learning and data mining methods have been used extensively to ?nd patterns in usage of the network by exploiting both contents and link structures. We have investigated these topics in a series of workshops on Semantic Web Mining (2001, 2002) at the European Conference on Machine Learning / Pr- ciples and Practice of Knowledge Discovery from Databases (ECML/PKDD) conference series, in the selection of papers for the post-proceedings of the - ropean Web Mining Forum 2003 Workshop, published as the Springer LNAI volume 3209 “Web Mining: From Web to Semantic Web” in 2004, as well as in the Knowledge Discovery and Ontologies workshop in 2004 and in the selection ofpapersfor thepost-proceedingsofthe ECML/PKDD2005jointworkshopson Web Mining (European Web Mining Forum) and on Knowledge Discovery and

There is generalagreementthat the quality of Machine Learning and Kno- edgeDiscoveryoutputstronglydependsnotonlyonthequalityofsourcedata andsophisticationoflearningalgorithms,butalsoonadditional,task/domain speci?c input provided by domain experts for the particular session. There is however less agreement on whether, when and how such input can and should e?ectively be formalized and reused as explicit prior knowledge. In the ?rst ofthe two parts into which the book is divided, we aimed to - vestigate current developments and new insights on learning techniques that exploit prior knowledge and on promising application areas. With respect to application areas, experiments on bio-informatics / medical and Web data environments are described. This part comprises a selection of extended c- tributionstothe workshopPrior Conceptual Knowledge inMachine Learning and Knowledge Discovery (PriCKL), held at ECML/PKDD 2007 18th - ropean Conference on Machine Learning and 11th European Conference on PrinciplesandPracticeofKnowledgeDiscoveryinDatabases).Theworkshop is part of the activities of the "SEVENPRO - Semantic Virtual Engineering for Product Design" project of the European 6th Framework Programme.The second part of the book has been motivated by the speci?cation of Web 2.0. We observe Web 2.0 as a powerful means of promoting the Web as a social medium, stimulating interpersonal communication and fostering the sharing of content, information, semantics and knowledge among people. Chapters are authored by participants to the workshop Web Mining 2.0, heldatECML/PKDD2007.Theworkshophostedresearchontheroleofweb mininginandfortheWeb2.0.Itispartoftheactivitiesoftheworkinggroups "UbiquitousData-InteractionandDataCollection"and"HumanComputer Interaction and Cognitive Modelling" of the Coordination Action "KDubiq - Knowledge Discovery in Ubiquitous Environments" of the European 6th Framework Programme.

Intelligent Information Access techniques attempt to overcome the limi- tions of current search devices by providing personalized information items and product/service recommendations. They normally utilize direct or in- rect user input and facilitate the information search and decision processes, according to user needs, preferences and usage patterns. Recent devel- ments at the intersection of Information Retrieval, Information Filtering, MachineLearning,UserModelling,NaturalLanguageProcessingandHuman- Computer Interaction o?er novel solutions that empower users to go beyond single-sessionlookuptasksandthataimatservingthemorecomplexrequi- ment: "Tell me what I don't know that I need to know". Information?ltering systems,speci?callyrecommendersystems,havebeenrevolutionizingtheway information seekers?nd what they want, becausethey e?ectively prune large informationspacesandhelpusersinselectingitemsthatbestmeettheirneeds and preferences. Recommender systems rely strongly on the use of various machine learning tools and algorithms for learning how to rank, or predict user evaluation, of items. Information Retrieval systems, on the other hand, also attempt to address similar ?ltering and ranking problems for pieces of information such as links, pages, and documents.But they generally focus on the development of global retrieval techniques, often neglecting individual user needs and preferences. The book aims to investigate current developments and new insights into methods, techniques and technologies for intelligent information access from a multidisciplinary perspective. It comprises six chapters authored by part- ipants in the research event Intelligent Information Access,heldinCagliari (Italy) in December 2008.

After the lesson learned during last years and following the successful edition of EC-Web 2009, for its 11th edition EC-Web tried to provide a clearer description of the electronic commerce universe focusing on some relevant topics. The main focus was not only on Internet-related techniques and approaches. The aim of EC-Web 2010 was to also cover aspects related to theoretical foundations of e-commerce, business processes as well as new approaches exploiting recently emerged technologies and scenarios such as the Semantic Web, Web services, SOA architectures, mobile and ubiquitous computing, just to cite a few. Due to their central role in any realistic e-commerce infrastructure, security and privacy issues were widely considered, without excluding legal and regulatory aspects. The choice of the above relevant topics directly reflects the fact that electronic commerce (EC), in the last few years, has changed and evolved into a well-established and founded reality both from a technological point of view and from a scientific one. Nevertheless, together with its evolution, new challenges and topics have emerged as well as new questions have been raised related to many aspects of EC. Keeping in mind the experience of the last edition of EC-Web, we maintained, for its 11th edition, the structure and the scientific organization of EC-Web 2009, aiming to highlight the autonomous role of the different (sometimes heterogeneous) aspects of EC, without missing their interdisciplinary scope.

Intelligent Information Access techniques attempt to overcome the limi- tions of current search devices by providing personalized information items and product/service recommendations. They normally utilize direct or in- rect user input and facilitate the information search and decision processes, according to user needs, preferences and usage patterns. Recent devel- ments at the intersection of Information Retrieval, Information Filtering, MachineLearning,UserModelling,NaturalLanguageProcessingandHuman- Computer Interaction o?er novel solutions that empower users to go beyond single-sessionlookuptasksandthataimatservingthemorecomplexrequi- ment: "Tell me what I don't know that I need to know". Information?ltering systems,speci?callyrecommendersystems,havebeenrevolutionizingtheway information seekers?nd what they want, becausethey e?ectively prune large informationspacesandhelpusersinselectingitemsthatbestmeettheirneeds and preferences. Recommender systems rely strongly on the use of various machine learning tools and algorithms for learning how to rank, or predict user evaluation, of items. Information Retrieval systems, on the other hand, also attempt to address similar ?ltering and ranking problems for pieces of information such as links, pages, and documents.But they generally focus on the development of global retrieval techniques, often neglecting individual user needs and preferences. The book aims to investigate current developments and new insights into methods, techniques and technologies for intelligent information access from a multidisciplinary perspective. It comprises six chapters authored by part- ipants in the research event Intelligent Information Access,heldinCagliari (Italy) in December 2008.

This volume focuses on new challenges in distributed Information Filtering and Retrieval. It collects invited chapters and extended research contributions from the DART 2011 Workshop, held in Palermo (Italy), on September 2011, and co-located with the XII International Conference of the Italian Association on Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world applications.The chapters of this book present a comprehensive review of related works and state of the art. Authors, both practitioners and researchers, shared their results in several topics such as "Multi-Agent Systems", "Natural Language Processing", "Automatic Advertisement", "Customer Interaction Analytics", "Opinion Mining".

This book constitutes the thoroughly refereed proceedings of the 21st International Conference on User Modeling, Adaption, and Personalization, held in Rome, Italy, in June 2013.

This volume focuses on new challenges in distributed Information Filtering and Retrieval. It collects invited chapters and extended research contributions from the special session on Information Filtering and Retrieval: Novel Distributed Systems and Applications (DART) of the 4th International Conference on Knowledge Discovery and Information Retrieval (KDIR 2012), held in Barcelona, Spain, on 4-7 October 2012.The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world applications. The chapters of this book present a comprehensive review of related works and state of the art. Authors, both practitioners and researchers, shared their results in several topics such as "Multi-Agent Systems", "Natural Language Processing", "Automatic Advertisement", "Customer Interaction Analytics", "Opinion Mining".Contributions have been careful reviewed by experts in the area, who also gave useful suggestions to improve the quality of the volume.

There is generalagreementthat the quality of Machine Learning and Kno- edgeDiscoveryoutputstronglydependsnotonlyonthequalityofsourcedata andsophisticationoflearningalgorithms,butalsoonadditional,task/domain speci?c input provided by domain experts for the particular session. There is however less agreement on whether, when and how such input can and should e?ectively be formalized and reused as explicit prior knowledge. In the ?rst ofthe two parts into which the book is divided, we aimed to - vestigate current developments and new insights on learning techniques that exploit prior knowledge and on promising application areas. With respect to application areas, experiments on bio-informatics / medical and Web data environments are described. This part comprises a selection of extended c- tributionstothe workshopPrior Conceptual Knowledge inMachine Learning and Knowledge Discovery (PriCKL), held at ECML/PKDD 2007 18th - ropean Conference on Machine Learning and 11th European Conference on PrinciplesandPracticeofKnowledgeDiscoveryinDatabases).Theworkshop is part of the activities of the "SEVENPRO - Semantic Virtual Engineering for Product Design" project of the European 6th Framework Programme.The second part of the book has been motivated by the speci?cation of Web 2.0. We observe Web 2.0 as a powerful means of promoting the Web as a social medium, stimulating interpersonal communication and fostering the sharing of content, information, semantics and knowledge among people. Chapters are authored by participants to the workshop Web Mining 2.0, heldatECML/PKDD2007.Theworkshophostedresearchontheroleofweb mininginandfortheWeb2.0.Itispartoftheactivitiesoftheworkinggroups "UbiquitousData-InteractionandDataCollection"and"HumanComputer Interaction and Cognitive Modelling" of the Coordination Action "KDubiq - Knowledge Discovery in Ubiquitous Environments" of the European 6th Framework Programme.

This volume focuses on new challenges in distributed Information Filtering and Retrieval. It collects invited chapters and extended research contributions from the DART 2011 Workshop, held in Palermo (Italy), on September 2011, and co-located with the XII International Conference of the Italian Association on Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world applications.The chapters of this book present a comprehensive review of related works and state of the art. Authors, both practitioners and researchers, shared their results in several topics such as "Multi-Agent Systems", "Natural Language Processing", "Automatic Advertisement", "Customer Interaction Analytics", "Opinion Mining".