Automatic Classification of Mobile Phone s Contacts

Sahami Shirazi, Alireza; Le, Huy Viet; Henze, Niels; Schmidt, Albrecht

Automatic Classification of Mobile Phone s Contacts

dc.contributor.author	Sahami Shirazi, Alireza	de
dc.contributor.author	Le, Huy Viet	de
dc.contributor.author	Henze, Niels	de
dc.contributor.author	Schmidt, Albrecht	de
dc.contributor.editor	Boll, Susanne
dc.contributor.editor	Maaß, Susanne
dc.contributor.editor	Malaka, Rainer
dc.date.accessioned	2017-11-22T14:54:40Z
dc.date.available	2017-11-22T14:54:40Z
dc.date.issued	2013
dc.description.abstract	Current smartphones have virtually unlimited space to store contact information. Users typically have dozens or even hundreds of contacts in their address book. The number of contacts can make it difficult to find particular contacts from the linear list provided by current phones. Grouping contacts ease the retrieval of particular contacts and also enables to share content with specific groups. Previous work, however, shows that users are not willing to manually categorize their contacts. In this paper we inves-tigate the automatic classification of contacts in phones contact lists, using the user s communication history. Potential contact groups were determined in an online survey with 82 participants. We collect-ed the call and SMS communication history from 20 additional participants. Using the collected data we trained a machine-learning algorithm that correctly classified 59.2% of the contacts. In a pilot study in which we asked participants to review the results of the classifier we found that 73.6% of the re-viewed contacts were considered correctly classified. We provide directions to further improve the performance and argue that the current results already enable to ease the manual classification of mo-bile phone contacts.	en
dc.identifier.isbn	978-3-486-77856-4
dc.identifier.uri	https://dl.gi.de/handle/20.500.12116/7492
dc.language.iso	en	en
dc.publisher	Oldenbourg Verlag
dc.relation.ispartof	Mensch & Computer 2013: Interaktive Vielfalt
dc.subject	mobile phone	de
dc.subject	machine learning	de
dc.subject	contact	de
dc.subject	facet	de
dc.title	Automatic Classification of Mobile Phone s Contacts	en
dc.type	muc: langbeitrag (vorträge)	en
gi.citation.endPage	36
gi.citation.publisherPlace	München
gi.citation.startPage	27	de_DE
gi.conference.sessiontitle	Session01: Kontextadaptive Systeme	de_DE
gi.document.quality	digidoc

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