Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
An empirical study of smoothing techniques for language modeling
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Positional language models for information retrieval
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
DivRank: the interplay of prestige and diversity in information networks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Topic models for image annotation and text illustration
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
How many words is a picture worth? Automatic caption generation for news images
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
A Statistical Approach for Automatic Text Summarization by Extraction
CSNT '11 Proceedings of the 2011 International Conference on Communication Systems and Network Technologies
Enriching textbooks with images
Proceedings of the 20th ACM international conference on Information and knowledge management
ImageHive: Interactive Content-Aware Image Summarization
IEEE Computer Graphics and Applications
Timeline generation through evolutionary trans-temporal summarization
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Text vs. images: on the viability of social media to assess earthquake damage
Proceedings of the 22nd international conference on World Wide Web companion
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Manual timelines have greatly helped us to keep pace with the big world. In this paper, we introduce a novel solution which generates image-text timelines for news events based on Evolutionary Image-Text Summarization, which is an important and challenging problem. We first extract image's semantic information under translation model, and then fuse the high quality images with text timeline under an image assignment algorithm which can optimize the global coordination of the final timeline. The experimental results show that news readers can receive more satisfaction from the image-text timelines we generate.