Frédérique Laforest

A comprehensive approach to model and use context for adapting applications in pervasive environments

With an increasing diversity of pervasive computing devices integrated in our surroundings and an increasing mobility of users, it will be important for computer systems and applications to be context-aware. Lots of works have already been done in this direction on how to capture context data and how to carry it to the application. Among the remaining challenges are to create the intelligence to analyze the context information and deduce the meaning out of it, and to integrate it into adaptable applications. Our work focuses on these challenges by defining generic context storage and processing model and by studying its impact on the application core. We propose a reusable context ontology model that is based on two levels: a generic level and a domain specific level. We propose a generic adaptation framework to guarantee adaptation of applications to the context in a pervasive computing environment. We also introduce a comprehensive adaptation approach that involves content adaptation and presentation adaptation inline with the adaptation of the core services of applications. Our case study shows that the context model and the application adaptation strategies provide promising service architecture.

Adaptation in Context-Aware Pervasive Information Systems: The SECAS Project

Purpose – The simple environment for context aware systems (SECAS) Project deals with the adaptation of applications to the context (user preferences and environment, terminal, etc.). The authors aim to develop a platform which makes the services, data and the user interface of applications adaptable to different context situations.Design/methodology/approach – Previous research has concentrated on how to capture context data and how to carry it to the application. The present work focuses on the impact of context on the application core. A case study in the medical field is also analysed.Findings – The paper illustrates a new definition of the context which separates the application data from the parameters of the context. This definition helps to establish a complete study on how to adapt applications on their three dimensions (services, content and presentation) to the context.Originality/value – The paper presents the SECAS platform, one that ensures the deployment of adaptive context‐aware applications.

A simple (yet powerful) algebra for pervasive environments

Querying non-conventional data is recognized as a major issue in new environments and applications such as those occurring in pervasive computing. A key issue is the ability to query data, streams and services in a declarative way. Our overall objective is to make the development of pervasive applications easier through database principles. In this paper, through the notion of virtual attributes and binding patterns, we define a data-centric view of pervasive environments: the classical notion of database is extended to come up with a broader notion, defined as relational pervasive environment, integrating data, streams and active/passive services. Then, the so-called Serena algebra is proposed with operators to homogeneously handle data and services. Moreover, the notion of stream can also be smoothly integrated into this algebra. A prototype of Pervasive Environment Management System has been implemented on which first experiments have been conducted to validate our approach.

Adaptation des applications au contexte en utilisant les services web

The SECAS Project (Simple Environment for Context Aware Systems) is interested in the adaptation of applications to the context (preferences and environment of the user, used terminal ...). We aim to develop a platform which makes the data, the services and the user interface of applications adaptable to the various context situations. In this domain, researches have concentrated on how to capture context data and to carry it to the application. Our work focuses on the impact of context on the application. In this paper, we present the architecture of SECAS, a new definition of the context, our adaptation strategy and a case of study in the medical field.

Real-time, scalable, content-based Twitter users recommendation

Real-time recommendation of Twitter users based on the content of their profiles is a very challenging task. Traditional IR methods such as TF-IDF fail to handle efficiently large datasets. In this paper we present a scalable approach that allows real time recommendation of users based on their tweets. Our model builds a graph of terms, driven by the fact that users sharing similar interests will share similar terms. We show how this model can be encoded as a compact binary footprint, that allows very fast comparison and ranking, taking full advantage of modern CPU architectures. We validate our approach through an empirical evaluation against the Apache Lucenes implementation of TF-IDF. We show that our approach is in average two hundred times faster than standard optimized implementation of TF-IDF with a precision of 58 %.

SoCQ: A Framework for Pervasive Environments

Querying non-conventional data sources is recognized as a major issue in new environments and applications such as those occurring in pervasive computing. A key issue is the ability to query data, streams and services in a declarative way. In this paper, we propose a framework that defines a data-centric view of pervasive environments: the classical notion of database is extended to come up with a broader notion, defined as relational pervasive environment, homogeneously integrating data, streams and active/passive services. It allows declarative definitions of service-oriented continuous queries using a SQL-like language, based on the so-called Serena algebra. We also tackle the design of a Pervasive Environment Management System that handles non-conventional data sources and service-oriented continuous queries.

Neural Wikipedian: Generating Textual Summaries from Knowledge Base Triples

Most people do not interact with Semantic Web data directly. Unless they have the expertise to understand the underlying technology, they need textual or visual interfaces to help them make sense of it. We explore the problem of generating natural language summaries for Semantic Web data. This is non-trivial, especially in an open-domain context. To address this problem, we explore the use of neural networks. Our system encodes the information from a set of triples into a vector of fixed dimensionality and generates a textual summary by conditioning the output on the encoded vector. We train and evaluate our models on two corpora of loosely aligned Wikipedia snippets and DBpedia and Wikidata triples with promising results.

C3PO: A Network and Application Framework for Spontaneous and Ephemeral Social Networks

The C3PO project promotes the development of new kind of social networks called Spontaneous and Ephemeral Social Networks (SESNs) dedicated to happenings such as cultural or sport events. SESNs rely on both opportunistic networks formed dynamically by the mobile devices of event attendees, and on an event-based communication model. Therefore, user can exchange digital contents with the other members of their SESNs, even without Internet access. This paper presents the framework developed in the C3PO project to provide network and application supports in such challenged networks. This framework exploits the different wireless interfaces of the mobile devices to interconnect them and to disseminate content through the resulting opportunistic network. At the application layer, this framework is composed of plugins that process locally the data stream to offer generic features, or to easily build applications dedicated to specific happenings.

Management of data sources and services in pervasive environments

Our daily environment contains more and more computerized devices, and tends to become a pervasive environment. Pervasive applications allow the end user to use a large number of heterogeneous devices, potentially invisible to him/her. To manage such kinds of applications, a distributed and modular architecture is required to handle the devices heterogeneity and their dynamicity, concerning their availability as well as the nature of data and services they can provide. In this article, we propose an architecture integrated in our SoCQ project [16] that builds an abstraction of the environment and thus simplifies the development of pervasive applications based on this abstraction. We also detail the current implementation of our architecture that includes the use of the UPnP technology.

Indexing semi-structured documents for context-based information retrieval in a medical information system

Most of the information retrieval models for documents are intended for SGML-like structured documents. In the context of medical informatics, the patient record document needs a looser structuration process as an a priori structure can hardly be defined. Thus we first propose an authoring tool that allows us to annotate embedded information, i.e. to give them a context, with qualifiers that are stored in a thesaurus rather than in SGML-like DTD. The retrieval process in the patient records collection takes into account the flexibility of the qualifying process while reformulating the queries.