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Auto-Personalitzation WAP Portal

Auto-Personalitzation WAP Portal
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Author(s): Jon T.S. Quah (Nanyang Technological University, Singapore)and Vincent L.H. Seet (Nanyang Technological University, Singapore)
Copyright: 2006
Pages: 7
Source title: Encyclopedia of E-Commerce, E-Government, and Mobile Commerce
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59140-799-7.ch003

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Abstract

WAP (wireless application protocol) has failed to take off exponentially as anticipated by industry players over the last few years with the slow acceptance by the consumers. The big players of WAP mobile phone manufacturers and mobile operators had over-hyped the advantages of using WAP to access the Internet ubiquitously. This had led to a mismatch in the consumers’ expectations when they eventually realized that user experience in surfing the Internet with WAP phones was not what was perceived earlier. The perceived experience was equated with that of surfing the Internet with desktop personal computers, browsing Web sites with rich multimedia contents. The reality is, WAP phones have limited screen real estate, and these came with monochrome displays initially. Thus, WAP contents have to be specially coded to suit the small screens for browsing. WAP phones with color displays were only available in quantity and variety since late 2002. Much of the WAP content available has not yet redesigned to take advantage of the new color displays. The attainable bandwidth for WAP surfing is only a small fraction when compared to broadband access. The bandwidth attainable by surfing WAP over GPRS (General Packet Radio Service, a 2.5-generation GSM packet data technology) is between 20 kbps to 40 kbps, whereas it is 256 kbps to 1,024 kbps for broadband. Prior to the availability of GPRS, WAP was carried over CSD (GSM Circuit Switch Data) and had an attainable bandwidth of merely 9.6 kbps. With these limiting factors, rich multimedia contents are simply not applicable to WAP at the moment (Gehlen & Bergs, 2004; Bai, Chou, Yen, & Lin, 2005). The limited screen real estate of WAP phones has also created navigation problems which involved many selections and too many moves between cards for consumers to achieve their goals. It was said that WAP is the “Wrong Approach to Portability,” and it is a technology designed by techies for techies, without the best interests of the consumer at heart (George & Sarch, 2001). Others said that WAP’s days were numbered and soon it would R.I.P. (rest in peace) (Saymour et al., 2001). It is certain that some amount of guidance is required for the less techie consumers during their initial encounters with WAP. Nevertheless, WAP is a good technology that allows one to access handy information in a timely fashion and ubiquitously. Like it or not, WAP will be around for some time, but much improvement is needed to make WAP surfing a less painful experience for consumers (Mahmoud, 2004; Sriskanthan, Meher, Ng, & Heng, 2004; Yeo, Hui, & Lee, 2004; Ma & Irvine, 2004; Radhamani & Siddiqi, 2004; Hung & Chang, 2005; Albastaki & Alajeeli, 2005; Gilbert & Han, 2005). Mobile Internet browsing using WAP phones has created unique problems of its kind. One of the challenges that consumers faced is that they are only equipped with a small screen for browsing WAP contents. This makes navigating to WAP sites of interest on WAP portals a hassle. WAP portals served as consumers’ gateway to the WAP sites offered by third-party content providers. These portals usually organize the list of WAP sites into a multilevel tree hierarchy structure. Consumers are required to navigate deep down the tree to access their favorite sites. This article proposes methods for making WAP portals adaptive. Such portals reduce time spent by consumers in navigation, hence there is more time for content browsing. The proposed methods do not require explicit consumers’ input for adaptation, but rather they implicitly track consumers’ navigation activities among WAP sites and use this input to form the basis of consumers’ preferences for adaptation. The methods had also taken into account possible drift of consumers’ interests over time, and weighted computation is used to achieve adaptation that will be of relevance to consumers at any point of time. Preliminary experiments with mobile users have yielded promising results.

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