This paper presents AES (acronym of Agents for EnrichedServices) framework; a generic framework that can be used to enrich services and adapting an original service request to what the context information, user profile and other multiple sources of information can bring in order to improve the end-user experience in using the framework. The framework is presented along with its architecture and the way it was implemented using agents, an example showing how this framework may improve collaboration and a study case are presented in order to validate the framework's functionality.

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One of the current challenges in information technology is to provide instant access to relevant information, without being limited by the location of the user or the device used to retrieve it. Current technologies allow users to access an overwhelming amount of data. This is an undesirable situation, since it is very difficult for users to obtain relevant information from these data. Enriching the user experience, which means, adding criteria such as user preferences and characteristics of his/her mobile context of use (e.g., location, access device features), can solve the aforementioned problem, since the information can be better adjusted to user needs and space-time situation, reducing the volume of information received by the user and avoiding information overloading. This paper presents an approach to enrich the user experience called Agents for Enrichment Services (AES), an adaptation framework based on agents that provides users with information tailored to their specific needs, features, devices, and context, with the purpose of giving relevant information at the right moment, place, and device.

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Purpose – This paper aims to present a detailed description of Agents for Enriching Services (AES), an agent-oriented framework that allows adapting a service in an information system. AES provides an adaptation logic that can be instantiated and extended to be useful in different domains. In previous works, we presented the adaptation mechanism of AES, which considers context aspects such as location, infrastructure; user aspects such as preferences and interests; and device aspects such as hardware and software features. Design/methodology/approach – The first step was the definition of different profiles, mainly user and context profiles. Then the adaptation mechanism was defined, which considers these profiles. With this mechanism, the adaptation filters to apply them to the initial queries was specified. Finally, feedback was provided, which included implicit and explicit information from the user and the system. AES is an agent-based framework implemented in Java, using the multi-agent platform BESA and a rule-based engine Drools. Findings – AES can be used as the starting point to adapt services by enriching them considering different stimulus whether they come from the environment, devices or user preferences. Research limitations/implications – This work was tested in an academic environment and was only applied to enhance queries by using keywords. AES uses the query mechanism implemented in the system that invokes it. Originality/value – This paper focuses on: an integrated view of AES including its formal description and details about its implementation. Particularly, it includes an exhaustive and formal definition of the filters used to create the adaptation rules and three different scenarios of the application of AES to adapt content according to user and context features. Finally, a comparison analysis is presented to highlight the strengths of our framework, specially its capacity of integration with systems that require providing user- and context-oriented services.