A young man is walking along the main street of a city, there are different shops and stores exposing their annotations by means of beacons. In particular, in the reference scenarios the following beacons will be used:
Each beacon contains a URL pointing to a semantic annotation in OWL (Web Ontology Language) sketched below in a graphical format.
The user is looking for a footwear shop. He defines the request, activates Bluetooh on his smartphone and finds the four exposed beacons. In this case, Superga shop obtains the highest rank because covers all features specified by the user. Zara obtains a lower score because the shop sells generic apparel products resulting more generic respect to the user requirements. McDonald's and Rossopomodoro receive a very low rank beacuse they are inappropriate for this request. Finally, detected beacons are ordered in a simple result activity list as shown in figure.
Now the user want to lunch with burger, pizza and salad in a fast-food.
In this scenario, Superga and Zara are inappropriate for the request whereas both McDonald's and Rossopomodoro partially cover the user request.
McDonald's is a fast-food but it has no pizza; Rossopomodoro also prepares pizza but is a restaurant (not a fast-food).
With a basic syntactic match, the two beacons would have the same score. Instead using a semantic-based rank and modelling the reference knowledge base properly, it is possible to highlight possible incompatibility between concepts. For example a restaurant is different from a fast-food, due to higher costs and waiting time, so Rossopomodoro (having an explicit incompatibility) should be more penalized respect to McDonald's only presenting missing features (Pizza).
Due to these reasons, the result list suggests McDonald's as most suitable solution.
In the evening, the user searches a restaurant to have dinner. In this case, Rossopomodoro completely covers the request whereas McDonald's only partially. As a result, Rossopomodoro will be the suggested location.