Probabilistic properties of a Markov-switching periodic GARCHGARCH process

summary:In this paper, we propose an extension of a periodic $GARCH$ ($PGARCH$) model to a Markov-switching periodic $GARCH$ ($MS$-$PGA$ $RCH$), and provide some probabilistic properties of this class of models. In particular, we address the question of strictly periodically and of weakly periodically stationary solutions. We establish necessary and sufficient conditions ensuring the existence of higher order moments. We further provide closed-form expressions for calculating the even-order moments as well as the autocovariances of the powers of a $MS$-$PGARCH$ process. We thus show how these moments and autocovariances can be used for estimating model parameters using $GMM$ method

GeomRDF: A Geodata Converter with a Fine-Grained Structured Representation of Geometry in the Web

In recent years, with the advent of the web of data, a growing number of national mapping agencies tend to publish their geospatial data as Linked Data. However, differences between traditional GIS data models and Linked Data model can make the publication process more complicated. Besides, it may require, to be done, the setting of several parameters and some expertise in the semantic web technologies. In addition, the use of standards like GeoSPARQL (or ad hoc predicates) is mandatory to perform spatial queries on published geospatial data. In this paper, we present GeomRDF, a tool that helps users to convert spatial data from traditional GIS formats to RDF model easily. It generates geometries represented as GeoSPARQL WKT literal but also as structured geometries that can be exploited by using only the RDF query language, SPARQL. GeomRDF was implemented as a module in the RDF publication platform Datalift. A validation of GeomRDF has been realized against the French administrative units dataset (provided by IGN France).Comment: 12 pages, 2 figures, the 1st International Workshop on Geospatial Linked Data (GeoLD 2014) - SEMANTiCS 201

An approach for measuring rdf data completeness

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An Adaptive Approach for Interlinking Georeferenced Data

International audienceThe resources published on the Web of data are often described by spatial references such as coordinates. The common data linking approaches are mainly based on the hypothesis that spatially close resources are more likely to represent the same thing. However, this assumption is valid only when the spatial references that are compared have been produced with the same positional accuracy, and when they actually represent the same spatial characteristic of the resources captured in an unambiguous way. Otherwise, spatial distance-based matching algorithms may produce erroneous links. In this article, we first suggest to formalize and acquire the knowledge about the spatial references, namely their positional accuracy, their geometric modeling, their level of detail, and the vagueness of the spatial entities they represent. We then propose an interlinking approach that dynamically adapts the way spatial references are compared, based on this knowledge

Alignment-based Partitioning of Large-scale Ontologies

Ontology alignment is an important task for information integration systems that can make different resources, described by various and heterogeneous ontologies, interoperate. However very large ontologies have been built in some domains such as medicine or agronomy and the challenge now lays in scaling up alignment techniques that often perform complex tasks. In this paper, we propose two partitioning methods which have been designed to take the alignment objective into account in the partitioning process as soon as possible. These methods transform the two ontologies to be aligned into two sets of blocks of a limited size. Furthermore, the elements of the two ontologies that might be aligned are grouped in a minimal set of blocks and the comparison is then enacted upon these blocks. Results of experiments performed by the two methods on various pairs of ontologies are promising

A Typology of Temporal Data Imperfection

International audienceTemporal data may be subject to several types of imperfection (e.g., uncertainty, imprecision..). In this context, several typologies of data imperfections have been already proposed. However, these typologies cannot be applied to temporal data because of the complexity of this type of data and the specificity that it contains. Besides, to the best of our knowledge, there is no typology of temporal data imperfections. In this paper, we propose a typology of temporal data imperfections. Our typology is divided into direct imperfections of both numeric temporal data and natural language based temporal data, indirect imperfections that can be deduced from the direct ones and granularity (i.e., context - dependent temporal data) which is related to several factors that can interfer in specifying the imperfection type such as person’s profile and multiculturalism. We finish by representing an example of imprecise temporal data in PersonLink ontology

Representing Imprecise Time Intervals in OWL 2

International audienceRepresenting and reasoning on imprecise temporal information is a common requirement in the field of Semantic Web. Many works exist to represent and reason on precise temporal information in OWL; however, to the best of our knowledge, none of these works is devoted to imprecise temporal time intervals. To address this problem, we propose two approaches: a crisp-based approach and a fuzzy-based approach. (1) The first approach uses only crisp standards and tools and is modelled in OWL 2. We extend the 4D-fluents model, with new crisp components, to represent imprecise time intervals and qualitative crisp interval relations. Then, we extend the Allen’s interval algebra to compare imprecise time intervals in a crisp way and inferences are done via a set of SWRL rules. (2) The second approach is based on fuzzy sets theory and fuzzy tools and is modelled in Fuzzy-OWL 2. The 4D-fluents approach is extended, with new fuzzy components, in order to represent imprecise time intervals and qualitative fuzzy interval relations. The Allen’s interval algebra is extended in order to compare imprecise time intervals in a fuzzy gradual personalized way. Inferences are done via a set of Mamdani IF-THEN rules