Riccardo Albertoni

Semantic similarity of ontology instances tailored on the application context

The paper proposes a framework to assess the semantic similarity among instances within an ontology It aims to define a sensitive measurement of semantic similarity, which takes into account different hints hidden in the ontology definition and explicitly considers the application context The similarity measurement is computed by combining and extending existing similarity measures and tailoring them according to the criteria induced by the context Experiments and evaluation of the similarity assessment are provided.

Asymmetric and context-dependent semantic similarity among ontology instances

In this paper we propose an asymmetric semantic similarity among instances within an ontology. We aim to define a measurement of semantic similarity that exploit as much as possible the knowledge stored in the ontology taking into account different hints hidden in the ontology definition. The proposed similarity measurement considers different existing similarities, which we have combined and extended. Moreover, the similarity assessment is explicitly parameterised according to the criteria induced by the context. The parameterisation aims to assist the user in the decision making pertaining to similarity evaluation, as the criteria can be refined according to user needs. Experiments and an evaluation of the similarity assessment are presented showing the efficiency of the method.

Visualization and semantic analysis of geographic metadata

The paper presents an approach based on visualization and ontology techniques to analyze large repository of geographic metadata: the aim of the metadata analysis is to support the search for expressive geographic resources. The approach is characterized by a visual reasoning to facilitate the navigation in an unfamiliar space of geographic metadata and a semantic reasoning to support the seeker in the definition of the search criteria. In particular, the analysis of categorical attributes of metadata is considered. Techniques and concepts of information visualization, graphic interaction and ontology are analyzed and exploited: the main principle of the approach is to integrate some of these techniques and concepts to facilitate data searching activity.

Semantic granularity for the semantic web

In this paper we describe a framework for the application of semantic granularities to the Semantic Web Given a data source and an ontology formalizing qualities which describe the source, we define a dynamic granularity system for the navigation of the repository according to different levels of detail, i.e., granularities Semantic granularities summarize the degree of informativeness of the qualities, taking into account both the individuals populating the repository, which concur in the definition of the implicit semantics, and the ontology schema, which gives the formal semantics The method adapts and extends to ontologies existing natural language processing techniques for topics generalization.

Environmental Thesauri under the Lens of Reusability

The development of a Spatial Data Infrastructure (SDI) at European level is strategic to answer the needs of environmental management requested by the European, national and local policies. Several European projects and initiatives aim to share, integrate and make accessible large amount of environmental data in order to overcome cross-border/language/cultural barriers. To this purpose, environmental thesauri are used as shared nomenclatures in metadata compilation and information discovery, and they are increasingly made available on the web. This paper provides a methodological approach for creating a catalogue of the environmental thesauri available on the web and assessing their reusability with respect to domain independent criteria. It highlights critical issues providing some recommendations for improving thesauri reusability.

Semantic similarity and selection of resources published according to linked data best practice

The position paper aims at discussing the potential of exploiting linked data best practice to provide metadata documenting domain specific resources created through verbose acquisition-processing pipelines. It argues that resource selection, namely the process engaged to choose a set of resources suitable for a given analysis/design purpose, must be supported by a deep comparison of their metadata. The semantic similarity proposed in our previous works is discussed for this purpose and the main issues to make it scale up to the web of data are introduced. Discussed issues contribute beyond the reengineering of our similarity since they largely apply to every tool which is going to exploit information made available as linked data. A research plan and an exploratory phase facing the presented issues are described remarking the lessons we have learnt so far.

Context dependent semantic granularity

A fundamental issue to improve the accessibility to information resources is how to efficiently deal with huge amount(s) of data. In this respect, ontology driven techniques are expected to improve the overlap between the Cognitive Space applied by the user and the Information Space, which is defined by the information providers. In this paper we describe a powerful method to extract semantic granularities, which enable the navigation of a repository according to different levels of abstraction. In the formalisation we present, granularities are explicitly parameterised according to criteria induced by the context, which improves the method flexibility. Furthermore, the parameterisation assists the user allowing to formulate and refine the browsing criteria. Case studies are described to demonstrate how granularities ease the information sources browsing and to illustrate how they may vary according to the context. A validation of the cognitive principles behind the method is presented, together with the analysis of the results obtained by the experimentation.

Context Enabled Semantic Granularity

In this paper we propose a powerful ontology driven method that eases the browsing of any repository of information resources described by an ontology: we provide a flexible semantic granularity method for the navigation of a repository according to different levels of abstraction, i.e. granularities. The granularity is explicitly parameterised according to the criteria induced by the context.

Overall quality assessment of SKOS thesauri: An AHP-based approach

The article proposes a methodology for a thesauri quality assessment that supports decision-makers in selecting thesauri by exploiting an overall quality measure. This measure takes into account the subjective perceptions of the decision-maker according to the reuse of thesauri in a specific application context. The analytic hierarchy process methodology is adopted to capture both subjective and objective facets involved in the thesauri quality assessment, thus providing a ranking of the thesauri assessed. Our methodology is applied to a set of thesauri by using user-driven application contexts. A step-by-step explanation of how the approach supports the decision process in the creation, maintenance and exploitation of a framework of linked thesauri is provided.

An ontology-driven search module for accessing chronic pathology literature

This paper presents an advanced search module for bibliography retrieval developed within the CHRONIOUS European IP project. The developed search module is specifically targeted to clinicians and healthcare practitioners searching for documents related to Chronic Obstructive Pulmonary Disease (COPD) and Chronic Kidney Disease (CKD). To this aim, the presented tool exploits two pathology-specific ontologies that allow focused document indexing and retrieval. Besides the search module, an enrichment tool is provided to maintain and to keep up-to date such as ontologies. In addition link with the terms of the MeSH (Medical Subject Heading) thesaurus has been provided to guarantee the coverage with the general certified medical terms and multilingual capabilities.