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Titlebook: Computational Collective Intelligence; 8th International Co Ngoc Thanh Nguyen,Lazaros Iliadis,Bogdan Trawiński Conference proceedings 2016

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發(fā)表于 2025-3-21 19:49:18 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computational Collective Intelligence
副標題8th International Co
編輯Ngoc Thanh Nguyen,Lazaros Iliadis,Bogdan Trawiński
視頻videohttp://file.papertrans.cn/233/232184/232184.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Collective Intelligence; 8th International Co Ngoc Thanh Nguyen,Lazaros Iliadis,Bogdan Trawiński Conference proceedings 2016
描述.This two-volume ?set (LNAI 9875 and LNAI 9876) constitutes therefereed proceedings of the 8th International Conference on CollectiveIntelligence, ICCCI 2016, held in Halkidiki, Greece, in September 2016..The 108 full papers presented were carefully reviewed and selected from 277 submissions.?.The aim of this conference is to provide an internationally respectedforum for scientific research in the computer-based methods ofcollective intelligence and their applications in (but not limited to)such fields as group decision making, consensus computing, knowledgeintegration, semantic web, social networks and multi-agent systems.?.
出版日期Conference proceedings 2016
關鍵詞collaborative computing; human computer interaction; machine learning; semantics and reasoning; social c
版次1
doihttps://doi.org/10.1007/978-3-319-45246-3
isbn_softcover978-3-319-45245-6
isbn_ebook978-3-319-45246-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2016
The information of publication is updating

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A Survey of ADAS Technologies for the Future Perspective of Sensor Fusionons that are based on sensor fusion are essential for the future. A short summary of capabilities of ADAS systems and selected ADAS modules was presented in this paper. The review was selected toward the future perspective of sensors fusion applied on the autonomous mobile platform.
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https://doi.org/10.1007/b100748ompared to the first model. We test also the solution against a network malfunction when some Access Points are turned off as the malfunction immunity is another important feature of the presented localization solution.
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Differential Evolution in a Recommendation System Based on Collaborative Filtering additional weights found by DE) generates the closest neighborhood for an active user, is used. The results of the experiment are compared with the linear measure of similarity Pearson’s correlation.
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