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CIKM
2010
Springer
13 years 6 months ago
You are where you tweet: a content-based approach to geo-locating twitter users
We propose and evaluate a probabilistic framework for estimating a Twitter user’s city-level location based purely on the content of the user’s tweets, even in the absence of ...
Zhiyuan Cheng, James Caverlee, Kyumin Lee
CHI
2011
ACM
12 years 11 months ago
Apolo: making sense of large network data by combining rich user interaction and machine learning
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
Duen Horng Chau, Aniket Kittur, Jason I. Hong, Chr...
CVPR
2008
IEEE
14 years 9 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
IPSN
2007
Springer
14 years 1 months ago
Sparse data aggregation in sensor networks
We study the problem of aggregating data from a sparse set of nodes in a wireless sensor network. This is a common situation when a sensor network is deployed to detect relatively...
Jie Gao, Leonidas J. Guibas, Nikola Milosavljevic,...
COMPGEOM
2004
ACM
14 years 1 months ago
Low-dimensional embedding with extra information
A frequently arising problem in computational geometry is when a physical structure, such as an ad-hoc wireless sensor network or a protein backbone, can measure local information...
Mihai Badoiu, Erik D. Demaine, Mohammad Taghi Haji...