Services for mobile and pervasive computingshould extensively exploit contextual information both toadapt to user needs and to enable autonomic behavior. Tofulfill this idea it is important to provide two key tools: amodel supporting context-data representation and manipulation,and a set of algorithms relying on the model toperform application tasks. Following these lines, we firstdescribe the W4 context model showing how it canrepresent a simple yet effective framework to enableflexible and general-purpose management of contextualinformation. In particular, we show the model suitability indescribing user-centric situations, e.g., describing situationsin terms of where a user is located and what he is doing.Then, we illustrate a set of algorithms to semanticallyenrich W4 represented data and to extract relevantinformation from it. In particular, starting from W4 data,such algorithms are able to identify the places that matter tothe user and to describe them semantically. Overall, weshow how the context-model and the algorithms allow tocreate an high-level, semantic and context-aware diarybasedservice. This service meaningfully collects andclassifies the user whereabouts and the places that the uservisited

Extracting High-Level Information from Location Data: the W4 Diary Example / Castelli, Gabriella; Mamei, Marco; Rosi, Alberto; Zambonelli, Franco. - In: MOBILE NETWORKS AND APPLICATIONS. - ISSN 1383-469X. - STAMPA. - 14:1(2009), pp. 107-119. [10.1007/s11036-008-0104-y]

Extracting High-Level Information from Location Data: the W4 Diary Example

CASTELLI, Gabriella;MAMEI, Marco;ROSI, Alberto;ZAMBONELLI, Franco
2009

Abstract

Services for mobile and pervasive computingshould extensively exploit contextual information both toadapt to user needs and to enable autonomic behavior. Tofulfill this idea it is important to provide two key tools: amodel supporting context-data representation and manipulation,and a set of algorithms relying on the model toperform application tasks. Following these lines, we firstdescribe the W4 context model showing how it canrepresent a simple yet effective framework to enableflexible and general-purpose management of contextualinformation. In particular, we show the model suitability indescribing user-centric situations, e.g., describing situationsin terms of where a user is located and what he is doing.Then, we illustrate a set of algorithms to semanticallyenrich W4 represented data and to extract relevantinformation from it. In particular, starting from W4 data,such algorithms are able to identify the places that matter tothe user and to describe them semantically. Overall, weshow how the context-model and the algorithms allow tocreate an high-level, semantic and context-aware diarybasedservice. This service meaningfully collects andclassifies the user whereabouts and the places that the uservisited
14
1
107
119
Extracting High-Level Information from Location Data: the W4 Diary Example / Castelli, Gabriella; Mamei, Marco; Rosi, Alberto; Zambonelli, Franco. - In: MOBILE NETWORKS AND APPLICATIONS. - ISSN 1383-469X. - STAMPA. - 14:1(2009), pp. 107-119. [10.1007/s11036-008-0104-y]
Castelli, Gabriella; Mamei, Marco; Rosi, Alberto; Zambonelli, Franco
File in questo prodotto:
File Dimensione Formato  
monet_final.pdf

non disponibili

Tipologia: Post-print dell'autore (bozza post referaggio)
Dimensione 242.63 kB
Formato Adobe PDF
242.63 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/609241
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 8
  • ???jsp.display-item.citation.isi??? 8
social impact