An architecture for the design of context-aware conversational agents

Proceedings of: 8th International Conference on Practical Applications of Agents and Multiagent Systems, Salamanca, Spain, April 26-28, 2010.In this paper, we present a architecture for the development of conversational agents that provide a personalized service to the user. The different agents included in our architecture facilitate an adapted service by taking into account context information and users specific requirements and preferences. This functionality is achieved by means of the introduction of a context manager and the definition of user profiles. We describe the main characteristics of our architecture and its application to develop and evaluate an information system for an academic domain.CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02- 02/TEC, SINPROB, CAM MADRINET S-0505/TIC/0255 and DPS2008-07029-C02-02.Publicad

Towards Activity Context using Software Sensors

Service-Oriented Computing delivers the promise of configuring and reconfiguring software systems to address user's needs in a dynamic way. Context-aware computing promises to capture the user's needs and hence the requirements they have on systems. The marriage of both can deliver ad-hoc software solutions relevant to the user in the most current fashion. However, here it is a key to gather information on the users' activity (that is what they are doing). Traditionally any context sensing was conducted with hardware sensors. However, software can also play the same role and in some situations will be more useful to sense the activity of the user. Furthermore they can make use of the fact that Service-oriented systems exchange information through standard protocols. In this paper we discuss our proposed approach to sense the activity of the user making use of software

Multi-Agent System (MAS) Applications in Ambient Intelligence (AmI) Environments

Proceedings of: 8th Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS`10). Salamanca (Spain), 28-30 April 2010Research in context-aware systems has been moving towards reusable and adaptable architectures for managing more advanced human-computer interfaces. Ambient. Intelligence (AmI) investigates computer-based services, which are ubiquitous and based on a variety of objects and devices. Their intelligent and intuitive interfaces act as mediators through which people can interact with the ambient environment. In this paper we present an agent-based architecture which supports the execution of agents in AmI environments. Two case studies are also presented, an airport information system and a railway information system, which uses spoken conversational agents to respond to the user's requests using the contextual information that includes the location information of the user.This work has been partially supported by CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, SINPROB, CAM MADRINET S-0505/TIC/0255 and DPS2008-07029-C02-02Publicad

A novel context ontology to facilitate interoperation of semantic services in environments with wearable devices

The LifeWear-Mobilized Lifestyle with Wearables (Lifewear) project attempts to create Ambient Intelligence (AmI) ecosystems by composing personalized services based on the user information, environmental conditions and reasoning outputs. Two of the most important benefits over traditional environments are 1) take advantage of wearable devices to get user information in a nonintrusive way and 2) integrate this information with other intelligent services and environmental sensors. This paper proposes a new ontology composed by the integration of users and services information, for semantically representing this information. Using an Enterprise Service Bus, this ontology is integrated in a semantic middleware to provide context-aware personalized and semantically annotated services, with discovery, composition and orchestration tasks. We show how these services support a real scenario proposed in the Lifewear project

Single-stranded DNA catenation mediated by human EVL and a type I topoisomerase

The human Ena/Vasp-like (EVL) protein is considered to be a bifunctional protein, involved in both actin remodeling and homologous recombination. In the present study, we found that human EVL forms heat-stable multimers of circular single-stranded DNA (ssDNA) molecules in the presence of a type I topoisomerase in vitro. An electron microscopic analysis revealed that the heat-stable ssDNA multimers formed by EVL and topoisomerase were ssDNA catemers. The ssDNA catenation did not occur when either EVL or topoisomerase was omitted from the reaction mixture. A deletion analysis revealed that the ssDNA catenation completely depended on the annealing activity of EVL. Human EVL was captured from a human cell extract by TOPO IIIα-conjugated beads, and the interaction between EVL and TOPO IIIα was confirmed by a surface plasmon resonance analysis. Purified TOPO IIIα catalyzed the ssDNA catenation with EVL as efficiently as the Escherichia coli topoisomerase I. Since the ssDNA cutting and rejoining reactions, which are the sub-steps of ssDNA catenation, may be an essential process in homologous recombination, EVL and TOPO IIIα may function in the processing of DNA intermediates formed during homologous recombination

Addressing the evolution of automated user behaviour patterns by runtime model interpretation

The final publication is available at Springer via http://dx.doi.org/10.1007/s10270-013-0371-3The use of high-level abstraction models can facilitate and improve not only system development but also runtime system evolution. This is the idea of this work, in which behavioural models created at design time are also used at runtime to evolve system behaviour. These behavioural models describe the routine tasks that users want to be automated by the system. However, users¿ needs may change after system deployment, and the routine tasks automated by the system must evolve to adapt to these changes. To facilitate this evolution, the automation of the specified routine tasks is achieved by directly interpreting the models at runtime. This turns models into the primary means to understand and interact with the system behaviour associated with the routine tasks as well as to execute and modify it. 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A Dynamic Contextual Change Management Application for Real Time Decision-Making Support

Decision making is a fundamental process within organizations for many reasons. It is indeed involved at all levels (new product decisions, management and marketing decisions, etc.) and has a direct impact on companies’ efficiency and effectiveness. Many researches are conducted to enhance the decision-making process by proposing decision support systems where the most frequent challenge is the change management. Indeed, all businesses operate within an environment that is subject to constant changes (like new customers’ needs and requirements, organisational and technological changes, changes in key information used to derive decisions, etc.). These changes have a major impact on the quality and accuracy of the proposed decision if they are not detected and propagated, at the right time, during the decision-making process. The present work attempts to resolve this challenge by proposing a dynamic change management technique that allows three tasks to be automatically performed. First, continuously detect changes and note them. Second, retrieve from the detected changes those that are related to the decision rules. Finally, propagate them by computing the new value of the decision rule. The proposal has been fully implemented and tested in the supervision process of gas network exploitation.projet FUI Gontran

OLAP queries context-aware recommender system

It becomes hard and tedious to easily obtain relevant decisional data in large data warehouses. In order to ease user exploration during on-line analytical processing analysis, recommender systems are developed. However some recommendations can be inappropriate (irrelevant queries or non-computable queries). To overcome these mismatches, we propose to integrate contextual data into the recommender system. In this paper, we provide (i) an indicator of obsolescence for OLAP queries and (ii) a context-aware recommender system based on a contextual post-filtering for OLAP queries