Michel Crampes

Ontology-supported and ontology-driven conceptual navigation on the World Wide Web

This paper presents the principles of ontology-supported and ontology-driven conceptual navigation. Conceptual navigation realizes the independence between resources and links to facilitate interoperability and reusability. An engine builds dynamic links, assembles resources under an argumentative scheme and allows optimization with a possible constraint, such as the users available time. Among several strategies, two are discussed in detail with examples of applications. On the one hand, conceptual specifications for linking and assembling are embedded in the resource meta-description with the support of the ontology of the domain to facilitate meta-communication. Resources are like agents looking for conceptual acquaintances with intention. On the other hand, the domain ontology and an argumentative ontology drive the linking and assembling strategies.

Survey on Social Community Detection

Community detection is a growing field of interest in the area of social network applications. Many community detection methods and surveys have been introduced in recent years, with each such method being classified according to its algorithm type. This chapter presents an original survey on this topic, featuring a new approach based on both semantics and type of output. Semantics opens up new perspectives and allows interpreting high-order social relations. A special focus is also given to community evaluation since this step becomes important in social data mining.

User centered and ontology based information retrieval system for life sciences

BackgroundBecause of the increasing number of electronic resources, designing efficient tools to retrieve and exploit them is a major challenge. Some improvements have been offered by semantic Web technologies and applications based on domain ontologies. In life science, for instance, the Gene Ontology is widely exploited in genomic applications and the Medical Subject Headings is the basis of biomedical publications indexation and information retrieval process proposed by PubMed. However current search engines suffer from two main drawbacks: there is limited user interaction with the list of retrieved resources and no explanation for their adequacy to the query is provided. Users may thus be confused by the selection and have no idea on how to adapt their queries so that the results match their expectations.ResultsThis paper describes an information retrieval system that relies on domain ontology to widen the set of relevant documents that is retrieved and that uses a graphical rendering of query results to favor user interactions. Semantic proximities between ontology concepts and aggregating models are used to assess documents adequacy with respect to a query. The selection of documents is displayed in a semantic map to provide graphical indications that make explicit to what extent they match the users query; this man/machine interface favors a more interactive and iterative exploration of data corpus, by facilitating query concepts weighting and visual explanation. We illustrate the benefit of using this information retrieval system on two case studies one of which aiming at collecting human genes related to transcription factors involved in hemopoiesis pathway.ConclusionsThe ontology based information retrieval system described in this paper (OBIRS) is freely available at: http://www.ontotoolkit.mines-ales.fr/ObirsClient/. This environment is a first step towards a user centred application in which the system enlightens relevant information to provide decision help.

Adaptive user interface for process control based on multi-agent approach

Teams of operators are required to monitor and control complex real-time processes. Process information comes from different sources and is often displayed by existing User Interfaces using a variety of visual and auditory forms and compressed into narrow time-windows. Most presentation modalities are fixed during interface design and are not capable of adaptation during system operation. The operators alone must provide the flexibility required in order to deal with difficult and unplanned situations. This paper presents an innovative Auto-Adaptive Multimedia Interface (AAMI) architecture, based on Intelligent Agent collaboration, designed to overcome the above drawbacks. The use of this technology should speed up the design and the implementation of human-centred multimedia interfaces, and significantly enhance their usability. The proposed architecture separates generic knowledge about adaptive user interface management from application specific knowledge in order to provide a generic framework suitable to be customised to different application domains. Benefits from the AAMI approach are evaluated by developing two industrial field-test application including Electrical Network Management and Thermal Plant Supervision system. The paper reports the architecture and the basic design principles of the generic framework as well details of the two applications. The work is being carried out within the European ESPRIT project: AMEBICA.

Concept Maps for Designing Adaptive Knowledge Maps

Concept Maps (CMaps) are an excellent method to visually represent and interact with a knowledge domain. A Knowledge Map (KMap) is a further complicated instance of a CMap, containing many instances of concepts and concept relations that add to the complexity of a visual representation. Adaptivity is also a key requirement for KMaps that we will demonstrate through practical example. This paper presents both a method, called ‘Domain-View-Controller’ (DVC) and a software environment specifically designed to create adaptive KMaps from CMaps. These tools give professional knowledge designers the means for specifying the domain knowledge of end users, allowing them to build well-organized adaptive KMaps with partial automated assistance. This paper also presents a scheme for the fully automated process of creating KMaps from domain specifications, giving end users the ability to display complex knowledge without having the expertise of knowledge engineers. The paper focuses on a real-world example from the domain of music to illustrate the underlying principles.

Ontological distance measures for information visualisation on conceptual maps

Finding the right semantic distance to be used for information research, classification or text clustering using Natural Language Processing is a problem studied in several domains of computer science We focus on measurements that are real distances: i.e that satisfy all the properties of a distance This paper presents one isa-distance measurement that may be applied to taxonomies This distance, combined with a distance based on relations other than isa, may be a step towards a real semantic distance for ontologies After presenting the purpose of this work and the position of our approach within the literature, we formally detail our isa-distance It is extended to other relations and used to obtain a MDS projection of a musical ontology in an industrial project The utility of such a distance in visualization, navigation, information research and ontology engineering is underlined.

Adaptive narrative abstraction

Narrative abstraction consists in selecting and assembling meaningful events from an original set of related events. This acquisition of information hinges on several requirements. This paper deals with some of them, namely the viewer’s intention, the viewer’s resource constraint, particularly the time constraint, and the narrative coherence. We present a foundation of narrative abstraction and several algorithms that can be used to build up abstracts compliant with the requirements. Our evaluation of these algorithms in a prototype leads to some questioning about their performance. We propose and discuss several solutions to improve them with regard to the flexibility of the abstract building process.

Automatic playlist composition in a dynamic music landscape

Music is both a social and a personal experience. Our goal is to automatically compose music playlists that combine the personal expectations of the listener with the expertise of professional playlist composers (or DJs). This paper begins by introducing an environment in the form of a music landscape that can be used for indexing music, navigating through a music collection and manually or automatically generating playlist. This paper briefly describes the first two issues and focuses on the last one. An evaluation of the environment and the process is then detailed, showing that although satisfied with the results produced, users want further possibilities of interaction and more semantic expressivity. We build on these user desires and provide new, more interactive landscapes. We conclude that playlist composition should not be left to computers alone and should require a high level human interaction, if not for necessity, at least for more pleasure.

An integrated visual approach for music indexing and dynamic playlist composition

This paper presents an innovative integrated visual approach for indexing music and automatically composing personalized playlists for radios or chain stores. To efficiently index hundreds of music titles by hand with artistic descriptors, the user only needs to drag and drop them onto a dynamic music landscape. To help the user we propose different dynamic visualization tools, such as the semantic spectrum and semantic field lenses. An algorithm then propagates artistic values that are hidden in the landscape into the titles being indexed. Different propagation algorithms are tested and compared. The dynamic composition methodology is then described with its class n-gram algorithm and its means for personalization based on the same music map as the visual indexing method. The new tools and techniques presented in this paper enable us to turn musical experience into an integrated visual experience that may generate new music knowledge and emotion.

From photo networks to social networks, creation and use of a social network derived with photos

With the new possibilities in communication and information management, social networks and photos have received plenty of attention in the digital age. In this paper, we show how social photos, captured during family events, representing individuals or groups, can be visualized as a network that reveals social attributes. From this photo network, social network is extracted that can help to build personalized albums. The photo network organization makes use of Formal Concept Analysis methods.