data mining

Enriching Data Lakes with Knowledge Graphs

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“Enriching Data Lakes with Knowledge Graphs” is a workshop paper published at “Knowledge Graph Generation from Text” co-located with ESWC 2022. Alessandro Chessa1,2, Gianni Fenu3, Enrico Motta4, Francesco Osborne4,5, Diego Reforgiato Recupero3,Angelo Antonio Salatino4, Luca Secchi1 1 Linkalab s.r.l., Cagliari, Italy 2 Luiss Data Lab, Rome, Italy 3 University of Cagliari, Cagliari, Italy 4 Knowledge Media Institute, The … Read more

Smart Topics Miner 2: Improving Proceedings Retrievability at Springer Nature

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Producing a robust and comprehensive representation of the research topics covered by a scientific publication is a crucial task that has a major impact on its retrievability and consequently on the diffusion of the relevant scientific ideas. Springer Nature, the world’s largest academic book publisher, has typically entrusted this task to the most expert editors, which had to manually analyse new books and produce a list of the most relevant topics. To support Springer Nature in this task, we developed Smart Topic Miner, an application that assists the editorial team in annotating proceedings books according to a large-scale ontology of research areas. Over the past three years, we evolved this application according to the editors’ feedback and developed a new engine, a new interface, and several other functionalities. In this demo paper, we present Smart Topic Miner 2, the most recent version of the tool, which is being regularly utilized by editors in Germany, China, Brazil, and Japan to annotate all book series covering conference proceedings in Computer Science, for a total of about 800 volumes per year.

Improving Editorial Workflow and Metadata Quality at Springer Nature

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Identifying the research topics that best describe the scope of a scientific publication is a crucial task for editors, in particular because the quality of these annotations determine how effectively users are able to discover the right content in online libraries. For this reason, Springer Nature, the world’s largest academic book publisher, has traditionally entrusted this task to their most expert editors. These editors manually analyse all new books, possibly including hundreds of chapters, and produce a list of the most relevant topics. Hence, this process has traditionally been very expensive, time-consuming, and confined to a few senior editors. For these reasons, back in 2016 we developed Smart Topic Miner (STM), an ontology-driven application that assists the Springer Nature editorial team in annotating the volumes of all books covering conference proceedings in Computer Science. Since then STM has been regularly used by editors in Germany, China, Brazil, India, and Japan, for a total of about 800 volumes per year. Over the past three years the initial prototype has iteratively evolved in response to feedback from the users and evolving requirements.

Supporting Springer Nature Editors by means of Semantic Technologies

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“Supporting Springer Nature Editors by means of Semantic Technologies” is a research paper accepted to the Industry Track at the International Semantic Web Conference (ISWC) 2017 , 21-25 October 2017, Vienna, Austria.

Authors

Francesco Osborne, Angelo Salatino, Thiviyan Thanapalasingam, Aliaksandr Birukou and Enrico Motta

Abstract

The Open University and Springer Nature have been collaborating since 2015 in the development of an array of semantically-enhanced solutions supporting editors in i) classifying proceedings and other editorial products with respect to the relevant research areas and ii) taking informed decisions about their marketing strategy. These solutions include i) the Smart Topic API, which automatically maps keywords associated with published papers to semantically characterized topics, which are drawn from a very large and automatically-generated ontology of Computer Science topics; ii) the Smart Topic Miner, which helps editors to associate scholarly metadata to books; and iii) the Smart Book Recommender, which assists editors in deciding which editorial products should be marketed in a specific venue.

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BigDat2017: a review

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This week I have been attending the 3rd edition of the Big Data winter school: BigDat2017. It was held in my former campus, at the University of Bari (IT). It was a really nice feeling to be back for a while, sitting on those benches and following courses, once again.
Big Data has recently gained a lot of interest in research and many believe that it will still play its leading role for many years. Nowadays, we live in a world in which all information seems to be available, we are surrounded by data-driven applications (Google, Facebook, Twitter, Spotify, just to name a few), which gather data and try to provide tailor-made solutions for their users. To this end, having such event like BigDat2017 with its clear mission —introduce and update new researchers into this fast advancing research area—is really important.

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Department Research Seminar: Early Detection of Research Topics

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On the 8th February I delivered a seminar to my department (KMi @ OU) in which I described the work I have been doing in the last two years for my postgraduate research.

I started with a little bit of introduction about science. Shortly, I moved to the currently available technologies for keeping track of the development of the different research areas. I showed how this technologies were not satisfactory enough if we want to perform an early detection of research topics.

In presenting, the state of the art (including The Structure of Scientific Revolution by Kuhn), I could state my main hypothesis, regarding the existence of an embryonic stage that research areas face, and that it is possible to detect their emergence during this stage1.

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Smart Topic Miner: Supporting Springer Nature Editors with Semantic Web Technologies

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STM interface

“Smart Topic Miner: Supporting Springer Nature Editors with Semantic Web Technologies” is poster paper presented at the Poster and Demo session [D45] on Wednesday 19th October 2016 at the 15th International Semantic Web Conference in Kobe, Japan

Authors:

Francesco Osborne, Angelo Antonio Salatino, Aliaksandr Birukou and Enrico Motta

Abstract:

Academic publishers, such as Springer Nature, annotate scholarly products with the appropriate research topics and keywords to facilitate the marketing process and to support (digital) libraries and academic search engines. This critical process is usually handled manually by experienced editors, leading to high costs and slow throughput. In this demo paper, we present Smart Topic Miner (STM), a semantic application designed to support the Springer Nature Computer Science editorial team in classifying scholarly publications.

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Automatic Classification of Springer Nature Proceedings with Smart Topic Miner

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Architecture of the system STM

 

“Automatic Classification of Springer Nature Proceedings with Smart Topic Miner” is conference paper presented on Friday 21st October 2016 at the 15th International Semantic Web Conference in Kobe, Japan

Authors:

Francesco Osborne, Angelo Antonio Salatino, Aliaksandr Birukou and Enrico Motta

Abstract:

The process of classifying scholarly outputs is crucial to ensure timely access to knowledge. However, this process is typically carried out manually by expert editors, leading to high costs and slow throughput. In this paper we present Smart Topic Miner (STM), a novel solution which uses semantic web technologies to classify scholarly publications on the basis of a very large automatically generated ontology of research areas. STM was developed to support the Springer Nature Computer Science editorial team in classifying proceedings in the LNCS family.

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Advanced Logistics for people and goods mobility: mathematical models and trials related to new protocols for mail delivery (LAMRECOR project)

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lamrecor
Infrastructure of the Project

 

Authors:

Mario Nicola Armenise, Vito Antonio Bevilacqua, Michele Bozzetti, Leonarda Carnimeo, Caterina Ciminelli, Marcello Di Marzo, Maria Grazia Dotoli, Maria Pia Fanti, Ivan Giannoccaro, Giuseppe Mastronardi, Michele Ottomanelli, Giulio Reina, Arcangelo Messina, Nicola Sasanelli, Lorenzo Abbatecola, Giuseppina Carlone, Massimiliano Dellisanti, Maripina De Palo, Filomena Innone, Angelo Antonio Salatino, Stefani Stipo, Teresa Tatoli, Marco Alessandris, Matteo Mottica, Alessandro Zizzari, Antonio Lorè, Salvatore Malerba

Abstract:

LAMRECOR project, funded by MiUR with Poste Italiane as prime contractor, aims at demonstrating an innovative integrated system for advanced logistics targeted at minimizing the environmental impact of the fleet of vehicles, at optimizing the productive processes, at improving the safety of the postal workers, and at developing new logistics procedures. For enhancing the safety of the workers, an integrated sensors system has been designed.

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