NDLI: In-depth Exploration of Geotagging Performance using Sampling Strategies on YFCC100M

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In-depth Exploration of Geotagging Performance using Sampling Strategies on YFCC100M

Content Provider	ACM Digital Library
Author	Kompatsiaris, Yiannis Kordopatis-Zilos, Giorgos Papadopoulos, Symeon
Abstract	Evaluating multimedia analysis and retrieval systems is a highly challenging task, of which the outcomes can be highly volatile depending on the selected test collection. In this paper, we focus on the problem of multimedia geotagging, i.e. estimating the geographical location of a media item based on its content and metadata, in order to showcase that very different evaluation outcomes may be obtained depending on the test collection at hand. To alleviate this problem, we propose an evaluation methodology based on an array of sampling strategies over a reference test collection, and a way of quantifying and summarizing the volatility of performance measurements. We report experimental results on the MediaEval 2015 Placing Task dataset, and demonstrate that the proposed methodology could help capture the performance of geotagging systems in a comprehensive manner that is complementary to existing evaluation approaches.
Starting Page	3
Ending Page	10
Page Count	8
File Format	PDF
ISBN	9781450345156
DOI	10.1145/2983554.2983558
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-10-16
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Evaluation Geotagging Social media
Content Type	Text
Resource Type	Article

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