DMCA
Curious Machines: Active Learning with Structured Instances (2008)
| Citations: | 11 - 1 self |
BibTeX
@TECHREPORT{Settles08curiousmachines:,
author = {Burr Settles},
title = {Curious Machines: Active Learning with Structured Instances},
institution = {},
year = {2008}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
and for Natalie, who now piques it. i ii Supervised machine learning is a branch of artificial intelligence concerned with automatically inducing predictive models from labeled data. Such learning approaches are useful for many interesting real-world applications, but particularly shine for tasks involving the automatic organization, extraction, and retrieval of information from large collections of data (e.g., text, images, and other digital media). In traditional supervised learning, one uses “labeled ” training data to induce a model. However, labeled instances for real-world applications are often difficult, expensive, or time consuming to obtain. Consider a complex task such as extracting key person and organization names from text documents. While gathering large amounts of unlabeled documents for these tasks is often relatively easy (e.g., from the World Wide Web), labeling these texts usually requires experienced human annotators with specific domain knowledge and training. There are implicit costs associated with obtaining these labels from domain experts, such as limited time and financial resources. This
Keyphrases
curious machine active learning structured instance specific domain knowledge real-world application many interesting real-world application learning approach complex task digital medium predictive model limited time traditional supervised learning automatic organization financial resource artificial intelligence large collection domain expert organization name implicit cost world wide web key person unlabeled document machine learning text document large amount experienced human annotator
