By Manuel Núñez, Ngoc Thanh Nguyen, David Camacho, Bogdan Trawiński
This two-volume set (LNAI 9329 and LNAI 9330) constitutes the refereed complaints of the seventh foreign convention on Collective Intelligence, ICCCI 2014, held in Madrid, Spain, in September 2015.
The one hundred ten complete papers provided have been conscientiously reviewed and chosen from 186 submissions. they're prepared in topical sections reminiscent of multi-agent structures; social networks and NLP; sentiment research; computational intelligence and video games; ontologies and knowledge extraction; formal tools and simulation; neural networks, SMT and MIS; collective intelligence in internet platforms – internet platforms research; computational swarm intelligence; cooperative techniques for choice making and optimization; complex networking and protection applied sciences; IT in biomedicine; collective computational intelligence in academic context; technological know-how intelligence and information research; computational intelligence in monetary markets; ensemble studying; significant info mining and searching.
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Extra info for Computational Collective Intelligence: 7th International Conference, ICCCI 2015, Madrid, Spain, September 21-23, 2015, Proceedings, Part II
2 Visual Saliency Visual saliency is deﬁned in  as the distinct subjective perceptual quality which makes some items in the world stand out from their neighbors and immediately grab our attention. The visual saliency process allows a human observer to specifically focus her/his attention on one or more visual stimuli into a scene depending on some semantic features like orientation, motion or color. It constitutes one of the most important properties of the human visual system (HVS) with numerous applications in digital imaging applications including content-aware video coding, segmentation or image resizing .
It is dynamically edited, it is very fast paced with very quickly uttered anchor comments. So, the dynamics of the “Teleexpress” News can be comparable to the dynamics of players scenes in TV sports news. However the number of topics and events reported in the news is usually much greater than in the sports news. The question is how the temporal aggregation method changes the temporal relations of shots, whether despite the fact that shots are aggregated their temporal characteristics enable us to predict a shot category.
Similarly to the began the news is finished with a final animation shot. The length of the intro and final animation is not constant, so after temporal segmentation at the beginning as well as at the end of a news video we can receive different sequence of shots. It is due to the fact that sometimes there is a fade from black to the intro part and the final animation usually fades away to a black frame. But we very often observed that the first frame of the intro or the last frame of the final animation are frozen, so the length of these parts of a news video are of an unpredictable duration.