Open AccessIntelligent Content Discovery on the Mobile Internet: Experiences and Lessons Learned
Author(s) -
Smyth Barry,
Cotter Paul,
Oman Stephen
Publication year - 2008
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v29i1.2083
Subject(s) - personalization , world wide web , computer science , usability , mobile web , the internet , software deployment , mobile technology , mobile business development , order (exchange) , mobile computing , revenue , mobile internet , mobile device , multimedia , internet privacy , telecommunications , business , human–computer interaction , accounting , finance , operating system
The mobile Internet represents a massive opportunity for mobile operators and content providers. Today there are more than 2 billion mobile subscribers, with 3 billion predicted by the end of 2007. However, despite significant improvements in handsets, infrastructure, content, and charging models, mobile users are still struggling to access and locate relevant content and services. An important part of this so‐called content‐discovery problem relates to the navigation effort that users must invest in browsing and searching for mobile content. In this article we describe one successfully deployed solution, which uses personalization technology to profile subscriber interests in order to automatically adapt mobile portals to their learned preferences. We present summary results, from our deployment experiences with more than 40 mobile operators and millions of subscribers around the world, which demonstrate how this solution can have a significant impact on portal usability, subscriber usage, and mobile operator revenues.