A conceptual framework for development of context-aware location-based services on smart-M3 platform

The paper presents a conceptual framework for development of context-aware location-based services. This framework provides relevant objects from the database to the user taking his/her preferences and context into account. It is based on the framework for context-aware preference queries, which provides a model of context- and preference-aware system based on the database, and the open source Smart-M3 platform, which allows to develop intelligent services using the smart space paradigm. The main components of the proposed framework include context-aware preference term generators that translate context information into context-aware preference terms, and a preference query executor that combines all preference terms and conducts their execution using PreferenceSQL JDBC driver. Evaluation of the proposed approach is made using the case study of context-aware restaurant data retrieval

A Context-Aware and Preference-Driven Vacation Planner for Tourism Regions

Taking a Preference SQL approach, a context-aware vacation planner for on-site activities is proposed to automatically generate vacation plans based on user preferences and situational aspects. Using different levels of abstraction, the result of the corresponding preference queries is always optimal and the result size is minimal. It consists of stereotype-specific and contextaware activities which are combined to create daily or even multi-day plans of activities. The correctness, completeness and optimality are assured by a preference calculus of strict partial orders. User preferences are initially collected and defined by a feedback questionnaire. The application is modelled by adequate preference compositions and the Preference SQL runtime system efficiently evaluates the resulting preference queries. The prototype proves that soft runtime requirements are met. Initial tests with real data from the industry-leading outdooractive platform indicate that the database-driven preference technology can successfully be employed to provide added value for vacation planning

The right expert at the right time and place: From expertise identification to expertise selection

We propose a unified and complete solution for expert finding in organizations, including not only expertise identification, but also expertise selection functionality. The latter two include the use of implicit and explicit preferences of users on meeting each other, as well as localization and planning as important auxiliary processes. We also propose a solution for privacy protection, which is urgently required in view of the huge amount of privacy sensitive data involved. Various parts are elaborated elsewhere, and we look forward to a realization and usage of the proposed system as a whole

An Evaluation of Faculty use of the Digital Library at Ankara University, Turkey

New consortial buying models have dramatically increased the availability of online resources, particularly journal articles, in the universities and technical institutes of developing countries. The degree of acceptance and pattern of use of such materials is of great interest to library collection development. Ankara University surveyed faculty members regarding their awareness and use of these electronic materials

Implanting Life-Cycle Privacy Policies in a Context Database

Ambient intelligence (AmI) environments continuously monitor surrounding individuals' context (e.g., location, activity, etc.) to make existing applications smarter, i.e., make decision without requiring user interaction. Such AmI smartness ability is tightly coupled to quantity and quality of the available (past and present) context. However, context is often linked to an individual (e.g., location of a given person) and as such falls under privacy directives. The goal of this paper is to enable the difficult wedding of privacy (automatically fulfilling users' privacy whishes) and smartness in the AmI. interestingly, privacy requirements in the AmI are different from traditional environments, where systems usually manage durable data (e.g., medical or banking information), collected and updated trustfully either by the donor herself, her doctor, or an employee of her bank. Therefore, proper information disclosure to third parties constitutes a major privacy concern in the traditional studies