Title: SIMCOP: a framework for similarity analysis of context histories

Authors: Tiago Wiedemann; Jorge Luis Victória Barbosa; Vítor Kehl Matter; Lucian Gonçales; Luan Carlos Nesi; Sandro José Rigo; Kleinner S.F. de Oliveira

Addresses: Applied Computing Graduate Program, University of Vale do Rio dos Sinos, São Leopoldo, RS, Brazil ' Applied Computing Graduate Program, University of Vale do Rio dos Sinos, São Leopoldo, RS, Brazil ' Applied Computing Graduate Program, University of Vale do Rio dos Sinos, São Leopoldo, RS, Brazil ' Applied Computing Graduate Program, University of Vale do Rio dos Sinos, São Leopoldo, RS, Brazil ' Applied Computing Graduate Program, University of Vale do Rio dos Sinos, São Leopoldo, RS, Brazil ' Applied Computing Graduate Program, University of Vale do Rio dos Sinos, São Leopoldo, RS, Brazil ' Applied Computing Graduate Program, University of Vale do Rio dos Sinos, São Leopoldo, RS, Brazil

Abstract: Ubiquitous computing studies ways to integrate technology into people's everyday life. It is an area that has been growing in recent years, primarily because of the development of technologies such as mobile computing. A key to the development of these applications is context awareness, which enables an application to self-adapt to the situation in which the user is on. This article proposes SIMCOP, a framework to develop applications based on similarity analysis of context histories. This analysis enables the identification of similar contexts to supply features such as the recommendation of entities and contexts, the entities' classification, and the prediction of contexts. We evaluated SIMCOP and discussed the results, through two evaluation applications, which suggest effectiveness in analysing the similarity in context histories. The main contribution of SIMCOP was the creation of an extensible and configurable architecture that allows combining different techniques of similarity analysis to find similarities between two sequences of contexts of generic entities.

Keywords: recommender system; ontology; contexts history; collaborative filtering.

DOI: 10.1504/IJBIS.2023.134955

International Journal of Business Information Systems, 2023 Vol.44 No.3, pp.339 - 367

Received: 11 Aug 2020
Accepted: 02 Nov 2020
Published online: 22 Nov 2023 *

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