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- 429 creator qiang-yang.
- 429 creator vincent-w-zheng.
- 429 creator xing-xie.
- 429 creator yu-zheng.
- 429 type InProceedings.
- 429 label "Collaborative Location and Activity Recommendations with GPS History Data".
- 429 sameAs 429.
- 429 abstract "With the increasing popularity of location-based services, such as tour guide and location-based social network, we now have accumulated many location data on the Web. In this paper, we show that, by using the location data based on GPS and users’ comments at various locations, we can discover interesting locations and possible activities that can be performed there for recommendations. Our research is highlighted in the following location-related queries in our daily life: 1) if we want to do something such as sightseeing or food-hunting in a large city such as Beijing, where should we go? 2) If we have already visited some places such as the Bird’s Nest building in Beijing’s Olympic park, what else can we do there? By using our system, for the first question, we can recommend her to visit a list of interesting locations such as Tiananmen Square, Bird’s Nest, etc. For the second question, if the user visits Bird’s Nest, we can recommend her to not only do sightseeing but also to experience its outdoor exercise facilities or try some nice food nearby. To achieve this goal, we first model the users’ location and activity histories that we take as input. We then mine knowledge, such as the location features and activity-activity correlations from the geographical databases and the Web, to gather additional inputs. Finally, we apply a collective matrix factorization method to mine interesting locations and activities, and use them to recommend to the users where they can visit if they want to perform some specific activities and what they can do if they visit some specific places. We empirically evaluated our system using a large GPS dataset collected by 162 users over a period of 2.5 years in the real-world. We extensively evaluated our system and showed that our system can outperform several state-of-the-art baselines.".
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- 429 keyword "Location Based Services".
- 429 title "Collaborative Location and Activity Recommendations with GPS History Data".
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- 430 creator chao-liu.
- 430 creator hung-chih-yang.
- 430 creator jinliang-fan.
- 430 creator li-wei-he.
- 430 creator yi-min-wang.
- 430 type InProceedings.
- 430 label "Distributed Non-negative Matrix Factorization for Web-Scale Dyadic Data Analysis on MapReduce".
- 430 sameAs 430.
- 430 abstract "Web abounds with dyadic data that keeps increasing by every single second. Previous work has repeatedly shown the usefulness of extracting the interaction structure inside dyadic data [20, 10, 9]. A commonly used tool in extracting the underlying structure is the matrix factorization, whose fame was recently boosted in the Netflix challenge [25]. When we were trying to replicate the same success on real-world Web dyadic data, we were seriously challenged by the scalability of available tools. We therefore in this paper report our efforts on scaling up the nonnegative matrix factorization (NMF) technique. We show that by carefully partitioning the data and arranging the computations to maximize data locality and parallelism, factorizing tens of millions by hundreds of millions matrices with billions of nonzero cells can be accomplished within tens of hours. Besides scalability, we also study the effectiveness of NMF on different Web dyadic data, which demonstrates the versatility of the proposed approach.".
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- 430 keyword "Efficient algorithms for large-scale analysis".
- 430 title "Distributed Non-negative Matrix Factorization for Web-Scale Dyadic Data Analysis on MapReduce".
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- 437 creator changhyun-lee.
- 437 creator haewoon-kwak.