Data stream processing algorithms

Part 2 book "Information processing in medical imaging" includes content: Imaging brain activation streams from optical flow computation on 2 riemannian manifolds, high level group analysis of FMRI data basedon dirichlet process mixture models, insight into efficient image registrationtechniques and the demons algorithm, divergence based framework for diffusion tensorclustering, interpolation and regularization,... and other contents.

382p muasambanhan07 20-02-2024 2 0   Download

Lecture Data mining: Lesson 19. The main topics covered in this chapter include: data stream mining and querying; data streams - computation model; data stream processing algorithms; probabilistic guarantees; computing stream sample; cash-register model;... Please refer to the content of document.

27p tieuvulinhhoa 22-09-2022 9 4   Download

Open issue trackers are a type of social media that has received relatively little attention from the text-mining community. We investigate the problems inherent in learning to triage bug reports from time-varying data. We demonstrate that concept drift is an important consideration. We show the effectiveness of online learning algorithms by evaluating them on several bug report datasets collected from open issue trackers associated with large open-source projects. We make this collection of data publicly available. ...

10p bunthai_1 06-05-2013 42 2   Download

Motivated by the recent interest in streaming algorithms for processing large text collections, we revisit the work of Ravichandran et al. (2005) on using the Locality Sensitive Hash (LSH) method of Charikar (2002) to enable fast, approximate comparisons of vector cosine similarity. For the common case of feature updates being additive over a data stream, we show that LSH signatures can be maintained online, without additional approximation error, and with lower memory requirements than when using the standard offline technique. ...

5p hongdo_1 12-04-2013 47 3   Download