Evaluating collaborative filtering content recommenders for mobile phones

Simple item page
dc.contributor.advisorChan, H Anthonyen_ZA
dc.contributor.authorPiyasena, Indika Weliwe Gamageen_ZA
dc.date.accessioned2014-07-31T10:54:04Z
dc.date.available2014-07-31T10:54:04Z
dc.date.issued2007en_ZA
dc.descriptionIncludes bibliographical references (leaves 64-67).
dc.description.abstractThe high adoption of mobile phones coupled with 3G technology can extend Internet access to new communities. Yet such access is currently impractical because mobile phone interfaces are cumbersome to use. In addition, hierarchical menus and search engines pose an interaction barrier to the unfamiliar. A content recommender is proposed to address these issues. Collaborative filtering is a technique developed to make predictions on unobserved items based on the preferences of similar users. User-based collaborative filtering has been identified as a simple, yet reasonably accurate scheme. An evaluation is conducted into how quickly this algorithm can identify preferred content based on user-content interactions.en_ZA
dc.identifier.apacitationPiyasena, I. W. G. (2007). <i>Evaluating collaborative filtering content recommenders for mobile phones</i>. (Thesis). University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering. Retrieved from http://hdl.handle.net/11427/5124en_ZA
dc.identifier.chicagocitationPiyasena, Indika Weliwe Gamage. <i>"Evaluating collaborative filtering content recommenders for mobile phones."</i> Thesis., University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering, 2007. http://hdl.handle.net/11427/5124en_ZA
dc.identifier.citationPiyasena, I. 2007. Evaluating collaborative filtering content recommenders for mobile phones. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Piyasena, Indika Weliwe Gamage AB - The high adoption of mobile phones coupled with 3G technology can extend Internet access to new communities. Yet such access is currently impractical because mobile phone interfaces are cumbersome to use. In addition, hierarchical menus and search engines pose an interaction barrier to the unfamiliar. A content recommender is proposed to address these issues. Collaborative filtering is a technique developed to make predictions on unobserved items based on the preferences of similar users. User-based collaborative filtering has been identified as a simple, yet reasonably accurate scheme. An evaluation is conducted into how quickly this algorithm can identify preferred content based on user-content interactions. DA - 2007 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2007 T1 - Evaluating collaborative filtering content recommenders for mobile phones TI - Evaluating collaborative filtering content recommenders for mobile phones UR - http://hdl.handle.net/11427/5124 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/5124
dc.identifier.vancouvercitationPiyasena IWG. Evaluating collaborative filtering content recommenders for mobile phones. [Thesis]. University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering, 2007 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/5124en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Electrical Engineeringen_ZA
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherElectrical Engineeringen_ZA
dc.titleEvaluating collaborative filtering content recommenders for mobile phonesen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
thesis_ebe_2007_piyasena_iwg (1).pdf
Size:
3.47 MB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Masters