Nonparametric user activity modelling and prediction
نویسندگان
چکیده
منابع مشابه
Prediction limits of mobile phone activity modelling
Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records fr...
متن کاملCompressed Nonparametric Language Modelling
Hierarchical Pitman-Yor Process priors are compelling for learning language models, outperforming point-estimate based methods. However, these models remain unpopular due to computational and statistical inference issues, such as memory and time usage, as well as poor mixing of sampler. In this work we propose a novel framework which represents the HPYP model compactly using compressed suffix t...
متن کاملUser Modelling for Intent Prediction in Information Analysis
User modelling is a key element in successfully assisting intelligence analysts who must gather information and make decisions without being overloaded by the massive amounts of data available on a daily basis most of which are irrelevant. Furthermore, with user modelling, we can predict the goals and intentions of the analyst in order to better serve their information seeking tasks by providin...
متن کاملSimultaneous Nonparametric Prediction Limits
Prediction limits are often attractive for carrying out multiple-comparisons-with-control hypothesis tests. We present algorithms for computing simultaneous confidence levels of partially sequential nonparametric prediction limit tests used in environmental monitoring. Algorithms are given for “pof-m” (m chances to get p observations “inbounds” at each of r locations to “pass”), “California” (e...
متن کاملChapter 16 Nonparametric Prediction
In this chapter we consider the prediction of stationary time series for various loss functions: squared loss (as it arises in the regression problem), 0− 1 loss (pattern recognition) and log utility (portfolio selection). The focus is on the construction of universal prediction rules, which are consistent for all possible stationary processes. Such rules can be obtained by combining elementary...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: User Modeling and User-Adapted Interaction
سال: 2020
ISSN: 0924-1868,1573-1391
DOI: 10.1007/s11257-020-09259-3