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» Fine Granular Aspect Analysis using Latent Structural Models
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ACL
2012
11 years 6 months ago
Fine Granular Aspect Analysis using Latent Structural Models
In this paper, we present a structural learning model for joint sentiment classification and aspect analysis of text at various levels of granularity. Our model aims to identify ...
Lei Fang, Minlie Huang
UAI
2004
13 years 5 months ago
Factored Latent Analysis for far-field Tracking Data
This paper uses Factored Latent Analysis (FLA) to learn a factorized, segmental representation for observations of tracked objects over time. Factored Latent Analysis is latent cl...
Chris Stauffer
ASPLOS
1996
ACM
13 years 8 months ago
Shasta: A Low Overhead, Software-Only Approach for Supporting Fine-Grain Shared Memory
This paper describes Shasta, a system that supports a shared address space in software on clusters of computers with physically distributed memory. A unique aspect of Shasta compa...
Daniel J. Scales, Kourosh Gharachorloo, Chandramoh...
ICIP
2006
IEEE
14 years 5 months ago
Unsupervised Image Layout Extraction
We propose a novel unsupervised learning algorithm to extract the layout of an image by learning latent object-related aspects. Unlike traditional image segmentation algorithms th...
David Liu, Datong Chen, Tsuhan Chen
ECTEL
2007
Springer
13 years 10 months ago
Scruffy Technologies to Enable (Work-integrated) Learning
Abstract. The goal of the APOSDLE (Advanced Process-Oriented SelfDirected Learning environment) project is to support work-integrated learning of knowledge workers. We argue that w...
Stefanie N. Lindstaedt, Peter Scheir, Armin Ulbric...