A conceptual model for data management in the field of ecology
A Latent Semantic Indexing-Based Approach to Determine Similar Clusters in Large-scale Schema Matching
An Approach to Controlling User Models and Personalization Effects in Recommender Systems
Combining Multiple Features for Web Data Sources Clustering
Resource-aware decomposition and orchestration of geoprocessing requests in a SOA framework
Semantic Content Processing in Web Portals
Service discovery with personal awareness in smart environments
Towards Leveraging Semantic Web Service Technology for Personalized, Adaptive Automatic Ubiquitous Sensors Discovery in Context of the Internet of Things.
Service discovery with personal awareness in smart environments
Title: | Service discovery with personal awareness in smart environments |
---|---|
Authors: | Kobkaew Opasjumruskit, Jesús Expósito, Birgitta König-Ries, Andreas Nauerz, Martin Welsch |
Source: | IGI Global - Creating Personal, Social, and Urban Awareness through Pervasive Computing |
Date: | 2013-10-01 |
Type: | Book Chapter |
Abstract: |
Web service descriptions with semantic web annotations can be exploited to automate dynamic discovery of services. The approaches introduced there aim at enabling automatic discovery, configuration, and execution of services in dynamic environments. In this chapter, we present the service discovery aspect of MERCURY, a platform for straightforward, user-centric integration and management of heterogeneous devices and services via a web-based interface. In the context of MERCURY, we use service discovery to find appropriate sensors, services, or actuators to perform a certain functionality required within a user-defined scenario, e.g., to obtain the temperature at a certain location, book a table at a restaurant close to the location of all friends involved, etc. A user will specify a service request, which will be fed to a matchmaker, which compares the request to existing service offers and ranks these offers based on how well they match the service request. In contrast to existing work, the service discovery approach we use is geared towards non-IT-savvy end users and is not restricted to single service-description formalism. Moreover, the matchmaking algorithm should be user-aware and environmentally adaptive, e.g. depending on the user’s location or surrounding temperature, rather than specific to simple keywords-based search which depends on the users’ expertise and mostly requires several tries. Hence, our goal is to develop a service discovery module on top of existing techniques, which shall rank discovered services to serve users’ queries according to their personal interests, expertise and current situations. |
File: | Service-discovery-with-personal-awareness-in-smart-environments_finalized.pdf |