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Exploiting contextual information to improve call prediction
With the increase in contact list size of mobile phone users, the management and retrieval of contacts has becomes a tedious job. In this study, we analysed some important dimensions that can effectively contribute in predicting which contact a user is going to call at time t. We improved a state of...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6808380/ https://www.ncbi.nlm.nih.gov/pubmed/31644590 http://dx.doi.org/10.1371/journal.pone.0223780 |
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author | Fatima, Mehk Rextin, Aimal Hayat, Shamaila Nasim, Mehwish |
author_facet | Fatima, Mehk Rextin, Aimal Hayat, Shamaila Nasim, Mehwish |
author_sort | Fatima, Mehk |
collection | PubMed |
description | With the increase in contact list size of mobile phone users, the management and retrieval of contacts has becomes a tedious job. In this study, we analysed some important dimensions that can effectively contribute in predicting which contact a user is going to call at time t. We improved a state of the art algorithm, that uses frequency and recency by adding temporal information as an additional dimension for predicting future calls. The proposed algorithm performs better in overall analysis, but more significantly there was an improvement in the prediction of top contacts of a user as compared to the base algorithm. |
format | Online Article Text |
id | pubmed-6808380 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-68083802019-11-02 Exploiting contextual information to improve call prediction Fatima, Mehk Rextin, Aimal Hayat, Shamaila Nasim, Mehwish PLoS One Research Article With the increase in contact list size of mobile phone users, the management and retrieval of contacts has becomes a tedious job. In this study, we analysed some important dimensions that can effectively contribute in predicting which contact a user is going to call at time t. We improved a state of the art algorithm, that uses frequency and recency by adding temporal information as an additional dimension for predicting future calls. The proposed algorithm performs better in overall analysis, but more significantly there was an improvement in the prediction of top contacts of a user as compared to the base algorithm. Public Library of Science 2019-10-23 /pmc/articles/PMC6808380/ /pubmed/31644590 http://dx.doi.org/10.1371/journal.pone.0223780 Text en © 2019 Fatima et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Fatima, Mehk Rextin, Aimal Hayat, Shamaila Nasim, Mehwish Exploiting contextual information to improve call prediction |
title | Exploiting contextual information to improve call prediction |
title_full | Exploiting contextual information to improve call prediction |
title_fullStr | Exploiting contextual information to improve call prediction |
title_full_unstemmed | Exploiting contextual information to improve call prediction |
title_short | Exploiting contextual information to improve call prediction |
title_sort | exploiting contextual information to improve call prediction |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6808380/ https://www.ncbi.nlm.nih.gov/pubmed/31644590 http://dx.doi.org/10.1371/journal.pone.0223780 |
work_keys_str_mv | AT fatimamehk exploitingcontextualinformationtoimprovecallprediction AT rextinaimal exploitingcontextualinformationtoimprovecallprediction AT hayatshamaila exploitingcontextualinformationtoimprovecallprediction AT nasimmehwish exploitingcontextualinformationtoimprovecallprediction |