A semantic context management framework on mobile device

We present a semantic context management framework named ContextTorrent, which can make various types of context information be semantically searchable and sharable among local and remote context-aware applications. We implement this framework on the Google Android platform with its elegant application support. An open source RDF parser has been extended to effectively get RDF triples from files or over the network. Three embedded database systems were evaluated for storing ontology represented contexts in the resource-constrained mobile devices. We use the FOAF ontology schema and a synthetic data set of up to 2500 records to evaluate the context query and storage performance. Ordinary context queries can be replied instantaneously.published_or_final_versionThe 6th IEEE International Conference on Embedded Software and Systems (ICESS 2009), Zhejiang, China, 25-27 May 2009. In Proceedings of the 6th ICESS, 2009, p. 331-33

On construction, performance, and diversification for structured queries on the semantic desktop

[no abstract

User context and personalized learning: a federation of contextualized attention metadata

Nowadays, personalized education is a very hot topic in technology enhanced learning (TEL) research. To support students during their learning process, the first step consists in capturing the context in which they evolve. Users typically operate in a heterogeneous environment when learning, including learning tools such as Learning Management Systems and non-learning tools and services such as e-mails, instant messaging, or web pages. Thus, user attention in a given context defines the Contextualized Attention Metadata (CAM). Various initiatives and projects allow capturing CAMs in a knowledge workers’ environment not only in the TEL area, but also in other domains like Knowledge Work Support, Personal Information Management and Information Retrieval. After reviewing main existing approaches according to some specific criteria that are of main interest for capturing and sharing user contexts, we present in this paper a framework able to gather CAMs produced by any tool or computer system. The framework is built on the Web-Based Enterprise Management (WBEM) standard dedicated to system, network and application management. Attention information specific to heterogeneous tools are represented as a unified and extensible structure, and stored into a central repository compliant with the above-mentioned standard. To facilitate access to this attention repository, we introduced a middleware layer composed of two dynamic services: the first service allows users to define the attention data they want to collect, whereas the second service is dedicated to receive and retrieve the traces produced by computer systems. An implementation for collecting and storing CAM data generated by the Ariadne Finder and Moodle validates our approach

Ontologiebasierte Indexierung und Kontextualisierung multimedialer Dokumente für das persönliche Wissensmanagement

Die Verwaltung persönlicher, multimedialer Dokumente kann mit Hilfe semantischer Technologien und Ontologien intelligent und effektiv unterstützt werden. Dies setzt jedoch Verfahren voraus, die den grundlegenden Annotations- und Bearbeitungsaufwand für den Anwender minimieren und dabei eine ausreichende Datenqualität und -konsistenz sicherstellen. Im Rahmen der Dissertation wurden notwendige Mechanismen zur semi-automatischen Modellierung und Wartung semantischer Dokumentenbeschreibungen spezifiziert. Diese bildeten die Grundlage für den Entwurf einer komponentenbasierten, anwendungsunabhängigen Architektur als Basis für die Entwicklung innovativer, semantikbasierter Lösungen zur persönlichen Dokumenten- und Wissensverwaltung.Personal multimedia document management benefits from Semantic Web technologies and the application of ontologies. However, an ontology-based document management system has to meet a number of challenges regarding flexibility, soundness, and controllability of the semantic data model. The first part of the dissertation proposes necessary mechanisms for the semi-automatic modeling and maintenance of semantic document descriptions. The second part introduces a component-based, application-independent architecture which forms the basis for the development of innovative, semantic-driven solutions for personal document and information management

PicShark: mitigating metadata scarcity through large-scale P2P collaboration

With the commoditization of digital devices, personal information and media sharing is becoming a key application on the pervasive Web. In such a context, data annotation rather than data production is the main bottleneck. Metadata scarcity represents a major obstacle preventing efficient information processing in large and heterogeneous communities. However, social communities also open the door to new possibilities for addressing local metadata scarcity by taking advantage of global collections of resources. We propose to tackle the lack of metadata in large-scale distributed systems through a collaborative process leveraging on both content and metadata. We develop a community-based and self-organizing system called PicShark in which information entropy—in terms of missing metadata—is gradually alleviated through decentralized instance and schema matching. Our approach focuses on semi-structured metadata and confines computationally expensive operations to the edge of the network, while keeping distributed operations as simple as possible to ensure scalability. PicShark builds on structured Peer-to-Peer networks for distributed look-up operations, but extends the application of self-organization principles to the propagation of metadata and the creation of schema mappings. We demonstrate the practical applicability of our method in an image sharing scenario and provide experimental evidences illustrating the validity of our approac

Augmenting Autobiographical Memory: An Approach Based on Cognitive Psychology

This thesis investigates how an interactive software system can support a person in remembering their past experiences and information related to these experiences. It proposes design recommendations for augmented autobiographical memory systems derived from Cognitive Psychology research into human memory – a perspective missing from prior work. Based on these recommendations, a conceptual design of an augmented autobiographical memory system is developed that aims to support users in retrieving cues and factual information related to experiences as well as in reconstructing those experiences. The retrieval aspects of this design are operationalised in an interactive software system called the Digital Parrot. Three important factors in the design and implementation are the context of an experience, semantic information about items in the system and associations between items. Two user studies evaluated the design and implementation of the Digital Parrot. The first study focused on the system's usability. It showed that the participants could use the Digital Parrot to accurately answer questions about an example memory data set and revealed a number of usability issues in the Digital Parrot's user interface. The second study embodied a novel approach to evaluating systems of this type and tested how an improved version of the Digital Parrot supported the participants in remembering experiences after an extended time period of two years. The study found that the Digital Parrot allowed the participants to answer questions about their own past experiences more completely and more correctly than unaided memory and that it allowed them to answer questions for which the participants' established strategies to counteract memory failures were likely to be unsuccessful. In the studies, associations between items were the most helpful factor for accessing memory-related information. The inclusion of semantic information was found to be promising especially in combination with textual search. Context was used to access information by the participants in both studies less often than expected, which suggests the need for further research. Identifying how to appropriately augment autobiographical memory is an important goal given the increasing volume of information to which users are exposed. This thesis contributes to achievement of this goal by stating the problem in Cognitive Psychology terms and by making design recommendations for augmented autobiographical memory systems. The recommendations are confirmed by the design and implementation of such a system and by empirical evaluations using an evaluation method appropriate for the field

PicShark: Mitigating Metadata Scarcity Through Large-Scale P2P Collaboration

Abstract With the commoditization of digital devices, personal information and media sharing is becoming a key application on the pervasive Web. In such a context, data annotation rather than data production is the main bottleneck. Metadata scarcity represents a major obstacle preventing effcient information processing in large and heterogeneous communities. However, social communities also open the door to new possibilities for addressing local metadata scarcity by taking advantage of global collections of resources. We propose to tackle the lack of metadata in large-scale distributed systems through a collaborative process leveraging on both content and metadata. We develop a community-based and self-organizing system called PicShark in which information entropy in terms of missing metadata is gradually alleviated through decentralized instance and schema matching. Our approach focuses on semi- structured metadata and confines computationally expensive operations to the edge of the network, while keeping distributed operations as simple as possible to ensure scalability. PicShark builds on structured Peer-to-Peer networks for distributed look-up operations, but extends the application of self-organization principles to the propagation of metadata and the creation of schema mappings. We demonstrate the practical applicability of our method in an image sharing scenario and provide experimental evidences illustrating the validity of our approach

Exploiting metadata for context creation and ranking on the desktop

[no abstract