Book ChapterDOI
CityVoyager: an outdoor recommendation system based on user location history
Yuichiro Takeuchi,Masanori Sugimoto +1 more
- pp 625-636
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TLDR
In this paper, a real-world recommendation system based on users' past location data history is proposed. But the system uses a newly devised place learning algorithm, which can efficiently find users' frequented places, complete with their proper names (e.g. “The Ueno Royal Museum”).Abstract:
Recommendation systems, which automatically understand user preferences and make recommendations, are now widely used in online shopping. However, so far there have been few attempts of applying them to real-world shopping. In this paper, we propose a novel real-world recommendation system, which makes recommendations of shops based on users’ past location data history. The system uses a newly devised place learning algorithm, which can efficiently find users’ frequented places, complete with their proper names (e.g. “The Ueno Royal Museum”). Users’ frequented shops are used as input to the item-based collaborative filtering algorithm to make recommendations. In addition, we provide a method for further narrowing down shops based on prediction of user movement and geographical conditions of the city. We have evaluated our system at a popular shopping district inside Tokyo, and the results demonstrate the effectiveness of our overall approach.read more
Citations
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Proceedings ArticleDOI
Mining interesting locations and travel sequences from GPS trajectories
TL;DR: This work first model multiple individuals' location histories with a tree-based hierarchical graph (TBHG), and proposes a HITS (Hypertext Induced Topic Search)-based inference model, which regards an individual's access on a location as a directed link from the user to that location.
Proceedings ArticleDOI
Map-matching for low-sampling-rate GPS trajectories
TL;DR: The results show that the ST-matching algorithm significantly outperform incremental algorithm in terms of matching accuracy for low-sampling trajectories and when compared with AFD-based global algorithm, ST-Matching also improves accuracy as well as running time.
Journal ArticleDOI
Collaborative Filtering beyond the User-Item Matrix: A Survey of the State of the Art and Future Challenges
TL;DR: A comprehensive introduction to a large body of research, more than 200 key references, is provided, with the aim of supporting the further development of recommender systems exploiting information beyond the U-I matrix.
Proceedings ArticleDOI
Collaborative location and activity recommendations with GPS history data
TL;DR: This paper shows that, by using the location data based on GPS and users' comments at various locations, it can discover interesting locations and possible activities that can be performed there for recommendations and extensively evaluated the system.
Proceedings ArticleDOI
Mining user similarity based on location history
TL;DR: A framework, referred to as hierarchical-graph-based similarity measurement (HGSM), is proposed for geographic information systems to consistently model each individual's location history and effectively measure the similarity among users and outperforms related similarity measures, such as the cosine similarity and Pearson similarity measures.
References
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Proceedings ArticleDOI
RADAR: an in-building RF-based user location and tracking system
TL;DR: RADAR is presented, a radio-frequency (RF)-based system for locating and tracking users inside buildings that combines empirical measurements with signal propagation modeling to determine user location and thereby enable location-aware services and applications.
Proceedings ArticleDOI
Item-based collaborative filtering recommendation algorithms
TL;DR: This paper analyzes item-based collaborative ltering techniques and suggests that item- based algorithms provide dramatically better performance than user-based algorithms, while at the same time providing better quality than the best available userbased algorithms.
Journal ArticleDOI
The active badge location system
TL;DR: A novel system for the location of people in an office environment is described, where members of staff wear badges that transmit signals providing information about their location to a centralized location service, through a network of sensors.
Journal ArticleDOI
Using collaborative filtering to weave an information tapestry
TL;DR: Tapestry is intended to handle any incoming stream of electronic documents and serves both as a mail filter and repository; its components are the indexer, document store, annotation store, filterer, little box, remailer, appraiser and reader/browser.
Proceedings ArticleDOI
Context-Aware Computing Applications
TL;DR: This paper describes systems that examine and react to an individual's changing context, and describes four catagories of context-aware applications: proximate selection, automatic contextual reconfiguration, contextual information and commands, and contex-triggered actions.