Exploratory analysis of textual data streams

In this paper, we address exploratory analysis of textual data streams and we propose a bootstrapping process based on a combination of keyword similarity and clustering techniques to: (i) classify documents into fine-grained similarity clusters, based on keyword commonalities; (ii) aggregate similar clusters into larger document collections sharing a richer, more user-prominent keyword set that we call topic; (iii) assimilate newly extracted topics of current bootstrapping cycle with existing topics resulting from previous bootstrapping cycles, by linking similar topics of different time periods, if any, to highlight topic trends and evolution. An analysis framework is also defined enabling the topic-based exploration of the underlying textual data stream according to a thematic perspective and a temporal perspective. The bootstrapping process is evaluated on a real data stream of about 330.000 newspaper articles about politics published by the New York Times from Jan 1st 1900 to Dec 31st 2015

Semantic Self-Formation of Communities of Peers

The formation of semantic communities of peers plays a crucial role for realizing effective query propagation mechanisms on a semantic basis. In this paper, we propose a novel approach to the self-organization of autonomous communities of peers; we propose semantic handshake techniques based on semantic community aggregation and community-aware query propagation techniques exploiting dynamic ontology matching techniques for improving traditional P2P search and discovery capabilities

introduction to social costs of diseases

Quando si parla di valutazioni economiche in sanità si intendono tipicamente delle analisi comparative, in termini di costi e di conseguenze, di programmi sanitari alternativi come l'introduzione di un nuovo farmaco, di una nuova apparecchiatura diagnostica o di una nuova terapia, confrontata con una situazione precedente o con un'altra alternativa (un altro farmaco, un'altra apparecchiatura diagnostica, un'altra terapia). Come si può evincere dalla tabella I (Gold et al., 1996), in realtà, esistono diverse tecniche di valutazione economica e solo alcune di esse corrispondono pienamente alla definizione appena fornita..

The HMatch 2.0 suite for ontology matchmaking

In this paper, we present the HMatch 2.0 suite for a exible and tailored ontology matchmaking, by focusing on the architectural features and on the evaluation results. Applications of HMatch 2.0 are also discussed, with special regard for the ontology evolution issues in the frame of the BOEMIE research project

Automatic identity recognition in the Semantic Web

The OKKAM initiative1 has recently highlighted the need of moving from the traditional web towards a \web of entities", where real-world objects descriptions could be retrieved, univocally identified, and shared over the web. In this paper, we propose our vision of the entity recognition problem and, in particular, we propose methods and techniques to capture the \identity" of a real entity in the Semantic Web. We claim that automatic techniques are needed to compare different RDF descriptions of a domain with the goal of automatically detect heterogeneous descriptions of the same real-world objects. Problems and techniques to solve them are discussed together with some experimental results on a real case study on web data

Semantic information interoperability in open networked system

In open networked systems, each node shares part of its informational resources on the network and is responsible of providing an ontological description for them. To enable semantic information interoperability in networked contexts with a multitude of autonomous ontologies, appropriate matching techniques are required to determine semantic mappings between concepts of different ontologies. In this paper, we describe H-Match, an algorithm for dynamically performing ontology matching in open networked contexts. H-Match provides several matching models and metrics to work at different levels of depth, with different degrees of flexibility and accuracy, thus supporting semantic interoperability in a flexible way

The CRIKE Data-Science Process for Legal Knowledge Extraction

In this paper, we present CRIKE, a data-science approach to automatically detect concrete applications of legal abstract terms in case-law decisions. To this purpose, CRIKE relies on the use of the LATO ontology where legal abstract terms are properly formalized as concepts and relations among concepts. Using LATO, CRIKE aims at discovering how and where legal abstract terms are applied by judges in their legal argumentation. Moreover, we detect the terminology used in the text of case-law decisions to characterize concrete abstract-term instances

Law Data Science and Ethics: the CRIKE Approach

In the era of big data, research activity on data science fo-cuses on large datasets to produce knowledge supporting decision-makingprocesses in different application domains and contexts. Data sciencepractices and outputs have a tremendous impact on a variety of fields byraising new ethical issues that become crucial. In this paper, we addressthe ethical issues related to the ethics of data, the ethics of algorithms,and the ethics of practices in the context of our data science approach forcase-law decisions (CLDs) processing called CRIKE (CRIme KnowledgeExtraction). In particular, we discuss the ethical issues that need to befaced when dealing with knowledge extracted from CLDs for descriptiveanalysis purposes and for predictive usage of data extracted from CLD

Results of the ontology alignment evaluation initiative 2019

The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity (from simple thesauri to expressive OWL ontologies) and use different evaluation modalities (e.g., blind evaluation, open evaluation, or consensus). The OAEI 2019 campaign offered 11 tracks with 29 test cases, and was attended by 20 participants. This paper is an overall presentation of that campaign