@inproceedings{823ceada6d7940a297fb9cae8b16d1e7,
title = "Tag filtering based on similar compatible principle",
abstract = "In social image sharing websites, users provide several descriptive tags to annotate their shared images. Usually, the raw tags are noisy, biased and incomplete. How to filter the tags is important for tag based applications. In this paper, a similar compatible principle based tag filtering approach is proposed. We classify tags into two sets. One is relevant to image content. The other is irrelevant to image content. We filter the tags by ranking high relevant tags ahead of the tags with low relevance by the similar compatible principle. This approach determines the ranks of user annotated tags by maximizing the compatible value of changing the labels of the tags from irrelevant to relevant at each step. Experiments on crawled Flickr dataset demonstrate the effectiveness of the proposed approach.",
keywords = "Flickr, Similar Compatible Principle, Social Image, Tag Ranking",
author = "Xueming Qian and Hua, \{Xian Sheng\} and Xingsong Hou",
year = "2012",
doi = "10.1109/ICIP.2012.6467368",
language = "英语",
isbn = "9781467325332",
series = "Proceedings - International Conference on Image Processing, ICIP",
pages = "2349--2352",
booktitle = "2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings",
note = "2012 19th IEEE International Conference on Image Processing, ICIP 2012 ; Conference date: 30-09-2012 Through 03-10-2012",
}