Through times, regions all over the world are very often subject to change (their names, their belonging, their composition, and their geometries). In this paper, we present a Semantic Matching Algorithm for automatically detecting, describing and publishing in the Linked Open Data Web, rich descriptions of changes occurring in multi-level territorial partitions (e.g., partitions made of major regions, regions and districts levels). We adopt a Linked Data (LD) approach for the semantic descriptions of the changes they undergo, relying on two existing generic ontologies, TSN-Ontology and TSN-Change Ontology. The created RDF graphs draw the lineage of each region over time (horizontal reading of the graphs), as well as the propagation of a change event through the partition levels (vertical reading).

In the recent years, photo context metadata (e.g.,date, GPS coordinates) have been proved to be useful in the management of personal photos. However, these metadata are still poorly considered in photo retrieving systems. In order to overcome this limitation, we propose an approach to incorporate contextual metadata in a keyword-based photo retrieval process.We use metadata about the photo shot context (address location, nearby objects, season, light status...) to generate a bag of words for indexing each photo. We extend the Vector Space Model in order to transform these shot context words into document-vector terms. In addition, spatial reasoning and geographical ontologies are used to infer new indexing terms. This facilitates the query-document matching process and also allows performing semantic comparison between the query terms and photo annotations.

This paper presents an approach for incorporating contextual metadata in a keyword-based photo retrieval process. We use our mobile annotation system PhotoMap in order to create metadata describing the photo shoot context (e.g., street address, nearby objects, season, lighting, nearby people...). These metadata are then used to generate a set of stamped words for indexing each photo. We adapt the Vector Space Model (VSM) in order to transform these shoot context words into document-vector terms. Furthermore, spatial reasoning is used for inferring new potential indexing terms. We define methods for weighting those terms and for handling a query matching. We also detail retrieval experiments carried out by using PhotoMap and Flickr geotagged photos. We illustrate the advantages of using Wikipedia georeferenced objects for indexing photos.

In this paper, we present a framework for context-based awareness support designed for Web-based groupware systems. Nowadays, such systems can be accessed through Web-enabled mobile devices, such as PDAs and cellular phones, which allow their users to perform simple tasks, such as contacting colleagues or reading messages. However, these devices present some constraints related to their intrinsic characteristics (reduced display size, limited memory capacity). These constraints make more acute the need for information filtering. We present a framework for awareness support which is able to adapt the awareness information to the user's context, in order to reduce the risk of information overload. This framework, called BW-M, selects among the available awareness information that which matches the user's, represented through pre-defined profiles, according to her/his current context.

The progress and the continuous evolution of computer capacities, as well as the emergence of the X3D standard have recently boosted the 3D domain. Associating some semantics with 3D contents becomes a major issue specially for reusing such contents or pieces of content after having extracted them from existing 3D scenes. In this paper, we address this issue by proposing a generic semantic annotation model for 3D, called 3DSEAM (3D semantics annotation model). 3DSEAM aims at indexing 3D contents considering visual, geometric and semantic aspects. 3DSEAM is instantiated using MPEG 7 that we have extended with 3D specific locators. These locators link some visual, geometric and semantic features to the corresponding X3D fragments. These features can then be used for indexing and querying.

The evolving desktop computer capacities and the emergence of the X3D standard offer a new boost to 3D domain. Giving sense to 3D content becomes a major issue specially for reusing such a content extracted from existing 3D scenes. In this paper, we address this issue by proposing a generic semantic annotation model for 3D called 3DSEAM (3D SEmantics Annotation Model). 3DSEAM aims at indexing 3D content considering visual, geometric and semantic aspects. 3DSEAM is instantiated using MPEG-7 extended with 3D specific locators. These locators link the visual, geometric and semantic features of a 3D content to the corresponding X3D fragment.

This paper addresses the adaptation of dynamic and synchronized multimedia presentations built by querying XML compatible data sources. We provide WIS designers with facilities for describing presentations whose content is not known at design time in terms of quantity, but only after the execution of queries. Our approach relies on the definition of a template. A template consists of a model that aims at automatically adapting the multimedia content of a presentation to both the user's profile and the characteristics of her/his access device. We show here how a template is built and how adaptations of the presentation are performed when the quantity of information and/or the material capabilities of the access devices (e.g. display size), do not match the template's spatiotemporal specifications.