In this paper, the authors discuss research on whether they can use Mechanical Turk (MTurk) to acquire goo annotations with respect to gold-standard data, whether they can filter out low-quality workers (spammers), and whether there is a learning effect associated with repeatedly completing the same kind of task.
This paper discusses anchor nodes placement for effective passive localization. The authors show that, for effective passive localization, the optimal placement of the anchor nodes is at the center of the network in such a way that no three anchor nodes share linearity.
Creator: Akl, Robert G.; Pasupathy, Karthikeyan & Haidar, Mohamad
This paper from the International Conference on Computational Science conference proceedings presents new methods that derive a new quality metric for automated scoring of quality of mucosa inspection performed by the endoscopist.
Date: May 31, 2010
Creator: Liu, Xuemin; Tavanapong, Wallapak; Wong, Johnny; Oh, JungHwan & de Groen, Piet C.
This paper analyzes the topic identification stage of single-document automatic text summarization across four different domains, consisting of newswire, literary, scientific and legal documents.
Date: June 2010
Creator: Ceylan, Hakan; Mihalcea, Rada, 1974-; Ozertem, Umut; Lloret, Elena & Palomar, Manuel
This paper introduces several extractive approaches for automatic image tagging, relying exclusively on information mined from texts. Through evaluations on two datasets, the authors show that their methods exceed competitive baselines by a large margin, and compare favorably with the state-of-the-art that uses both textual and image features.
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