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

Anti-Phospholipase A2 Receptor Antibodies in Membranous Nephropathy : from Bench to the Patient

Membranous Nephropathy (MN) is the leading cause of nephrotic syndrome in adults. Primary or idiopathic Membranous Nephropathy (iMN) has been considered as an organ-specific autoimmune disease with an unknown aetiology. By contrast, secondary membranous nephropathy has been described as the expression of a systemic autoimmune response to malignancy or bacterial/viral infections. In the majority of iMN cases, glomerular lesions are determined by autoantibodies against a podocyte membrane protein, the M-type of phospholipase A2 receptor 1 (PLA2R1). Several studies have suggested that the detection of anti-PLA2R1 in patients sera with nephrotic syndrome may be pathognomonic of iMN, thus obviating the need for a diagnostic renal biopsy and an extensive workup for underlying causes. Many authors inferred that the measurement of anti-PLA2R1 may change the diagnostic algorithm in patients with nephrotic syndrome and guide treatment decisions in patients with iMN. Measurement of anti-PLA2R1 antibodies is now possible through an easy to use, commercially available assay. The aim of this review is to describe the clinical relevance of anti-PLA2R1 assessment in patients with MN, and to extensively discuss the biotechnological methods available to measure them

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

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

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

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