Social Approach for Context Analysis: Modelling and Predicting Social Network Evolution using Homophily
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Yksityiskohdat
| Alkuperäiskieli | Englanti |
|---|---|
| Otsikko | Modeling and Using Context |
| Alaotsikko | 9th International and Interdisciplinary Conference, CONTEXT 2015, Lanarca, Cyprus, Novemer 2-6,2015. Proceedings |
| Kustantaja | Springer International Publishing |
| Sivut | 513-519 |
| Sivumäärä | 7 |
| ISBN (elektroninen) | 978-3-319-25591-0 |
| ISBN (painettu) | 978-3-319-25590-3 |
| DOI - pysyväislinkit | |
| Tila | Julkaistu - 2015 |
| OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisussa |
| Tapahtuma | International and Interdisciplinary Conference on Modeling and Using Context - Kesto: 1 tammikuuta 1900 → … |
Julkaisusarja
| Nimi | Lecture Notes in Artificial Intelligence |
|---|---|
| Vuosikerta | 9405 |
Conference
| Conference | International and Interdisciplinary Conference on Modeling and Using Context |
|---|---|
| Ajanjakso | 1/01/00 → … |
Tiivistelmä
Understanding the user’s context is important for mobile applications to provide personalized services. Such context is typically based on the user’s own information. In this paper, we show how social network analysis and the study of the individual in a social network can provide meaningful contextual information. According to the phenomenon of homophily, similar users tend to be connected more frequently than dissimilar. We model homophily in social networks over time. Such models strengthen context inference algorithms, which helps determine future status of the user, resulting in prediction accuracy improvements of up to 118% with respect to a naïve classifier.