Towards semantic alignment of heterogeneous structures and its application to digital humanities

Different variants of the notion of ‘alignment’ have been adopted in a range of areas, focusing on homogeneous structures (e.g., text alignment [8], database alignment [1] or ontology alignment [4]) or heterogeneous structures (e.g., annotation of text with on- tologies [3], alignment of dictionaries and ontologies [2], alignments between relational databases and ontologies [9]). These alignment approaches, however, take little account of the alignment of multiple structures. This type of approach is becoming increasingly necessary to manage the growing volume of unstructured information sources available on the Web (encyclopedias such as Wikipedia, social media data, etc.) and LOD knowl- edge bases. In addition, the approaches are mostly developed for the English language. These needs have to be addressed through a global vision of alignment that takes into account a multiplicity of structures in which knowledge can be expressed. This paper seeks a holistic approach to semantic computing and alignment, when considering het- erogeneous structures in which knowledge is represented.FCT CEECIND/01997/2017, UIDB/00057/202

Taking advantage of discursive properties for validating hierarchical semantic relations from parallel enumerative structures

This paper presents an approach for automatically validating candidate hierarchical relations extracted from parallel enumerative structures. It relies on the discursive properties of these structures and on the combination of resources of diéerent nature, a semantic network and a distributional resource. The results show an accuracy of between 0.50 and 0.67, with a gain of 0.11 when combining the two resources

Explaining Argumentation over Alignment Agreements

International audienceArgumentation frameworks have been used as tools for reconciliating ontology alignments, through a series of proposals and counter-proposals, i.e., arguments. However, argumentation outcomes may not be so obvious to human users. Explaining the reasoning behind the argumentation process may help users to understand its outcome, and influence the user's confidence and acceptance on the results. This paper presents a mechanism for providing explanations on the way agreed alignments are established. Our mechanism is based on tracing each step of the argumentation process. These traces are then interpreted using a set of association rules, built from a decision tree that represents all possible statuses of arguments. From these rules, a multi-level explanation, in natural language, is provided to the users

PLATAL - a tool for web hierarchies extraction and alignment

International audienceThis paper presents PLATAL, a modular and extensible toolfor extraction of hierarchical structures from web pages which can be automatically aligned and also manually edited via a graphical interface. Evaluation of alignments can be carried out using standard measures

VOAR: A Visual and Integrated Ontology Alignment Environment

International audienceOntology alignment is a key process for enabling interoperability between ontology-based systems in the Linked Open Data age. From two input ontologies, this process generates an alignment (set of correspondences) between them. In this paper we present VOAR, a new web-based environment for ontology alignment visualization and manipulation. Within this graphical environment, users can manually create/edit correspondences and apply a set of operations on alignments (filtering, merge, difference, etc.). VOAR allows invoking external ontology matching systems that implement a specific alignment interface, so that the generated alignments can be manipulated within the environment. Evaluating multiple alignments together against a reference one can also be carried out, using classical evaluation metrics (precision, recall and f-measure). The status of each correspondence with respect to its presence or absence in reference alignment is visually represented. Overall, the main new aspect of VOAR is the visualization and manipulation of alignments at schema level, in an integrated, visual and web-based environment

Rewriting SELECT SPARQL queries from 1:n complex correspondences

This paper presents a mechanism for rewriting SPARQL queries based on complex ontology correspondences. While the usefulness of simple correspondences, involving single entities from both source and target ontologies, has long been recognized, query rewriting requires more expressive links between ontology entities expressing the true relationships between them. Here, complex correspondences, in the format 1:n, between overlapping ontologies are exploited for rewriting SELECT SPARQL queries, so that they can be expressed over different RDF data sets in the Linked Open Data. Our approach has been evaluated using two data sets, one from the agriculture domain and another based on a reduced set involving the ontologies from the OAEI Conference track

Complex correspondences for query patterns rewriting

International audienceThis paper discusses the use of complex alignments in the task of automatic query patterns rewriting. We apply this approach in SWIP, a system that allows for querying RDF data from natural language-based queries, hiding the complexity of SPARQL. SWIP is based on the use of query patterns that characterise families of queries and that are instantiated with respect to the initial user query expressed in natural language. However, these patterns are specific to the vocabulary used to describe the data source to be queried. For rewriting query patterns, we experiment ontology matching approaches in order to find complex correspondences between two ontologies describing data sources. From the alignments and initial query patterns, we rewrite these patterns in order to be able to query the data described using the target ontology. These experiments have been carried out on an ontology on the music domain and DBpedia ontology

Towards an Ontology-based Approach for Heterogeneous Model Matching

International audienceThe overall goal of our approach is to relate models-of a given domain that are designed by different actors in different Domain Specific Languages , and thus are heterogeneous. Instead of building a single global model, we propose to organize the different source models as a network of models, which provides a global view of the system through a correspondence model. This latter, conform to a correspondence meta-model is built via a manual matching process. In this paper we explore the possibility of representing models as ontologies and take advantage of an automated process to match them.in order to enhance the automation of the matching process

Analysing top-level and domain ontology alignments from matching systems

Top-level ontologies play an important role in the construction and integration of domain ontologies, providing a well-founded reference model that can be shared across knowledge domains. While most efforts in ontology matching have been particularly dedicated to domain ontologies, the problem of matching domain and top-level ontologies has been addressed to a lesser extent. This is a challenging task, specially due to the different levels of abstraction of these ontologies. In this paper, we present a comprehensive analysis of the alignments between one domain ontology from the OAEI Conference track and three well known top-level ontologies (DOLCE, GFO and SUMO), as generated by a set of matching tools. A discussion of the problem is presented on the basis of the alignments generated by the tools, compared to the analysis of three evaluators. This study provides insights for improving matching tools to better deal with this particular task