NDLI: Activity-based serendipitous recommendations with the Magitti mobile leisure guide (2008)

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Activity-based serendipitous recommendations with the Magitti mobile leisure guide (2008)

Content Provider	CiteSeerX
Author	Bellotti, Victoria Begole, Bo Chi, H. Ducheneaut, Nicolas Fang, Ji Isaacs, Ellen King, Tracy Newman, Mark W. Partridge, Kurt Price, Bob Rasmussen, Paul Roberts, Michael Schiano, Diane J. Walendowski, Alan
Description	In ACM CHI This paper presents a context-aware mobile recommender system, codenamed Magitti. Magitti is unique in that it infers user activity from context and patterns of user behavior and, without its user having to issue a query, automatically generates recommendations for content matching. Extensive field studies of leisure time practices in an urban setting (Tokyo) motivated the idea, shaped the details of its design and provided data describing typical behavior patterns. The paper describes the fieldwork, user interface, system components and functionality, and an evaluation of the Magitti prototype. Author Keywords Field studies, user experience design, interaction, context-aware computing, mobile recommendation systems, leisure. ACM Classification Keywords H5.m. Information interfaces and presentation (e.g., HCI):
File Format	PDF
Language	English
Publisher Date	2008-01-01
Access Restriction	Open
Subject Keyword	Urban Setting Context-aware Mobile Recommender System User Experience Design Magitti Prototype Extensive Field Study User Interface Information Interface System Component Author Keywords Field Study Mobile Recommendation System Context-aware Computing Typical Behavior Pattern User Behavior User Activity Magitti Mobile Leisure Guide Leisure Time Practice Activity-based Serendipitous Recommendation Acm Classification Keywords H5 Content Matching
Content Type	Text
Resource Type	Article

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