منابع مشابه
Guest Editorial: Big Social Data Analysis
In the era of social connectedness, Web users are becoming increasingly enthusiastic about interacting, sharing, and collaborating through online collaborative media. In recent years, this collective intelligence has spread to many different areas, with particular focus on fields related to everyday life such as commerce , tourism, education, and health, causing the size of the social Web to ex...
متن کاملGuest Editorial: Big Data Analytics and the Web
THE paper by Shao et al., “Clustering Big SpatiotemporalInterval Data,” focuses on clustering big spatiotemporal data, which are common in the emerging Web of Things (WoT), where a large number of sensors are deployed for continuously collecting data. The authors explore a novel way to cluster massive Web data with spatiotemporal intervals in multiple Euclidean spaces, as well as a new energy f...
متن کاملGuest Editorial: Big Media Data: Understanding, Search, and Mining
BIG media data is a new research area, and has been attracting a lot of research interests in both industry and academia. This editorial, as the third part of this special issue, introduces two papers on video copy detection data and personalized travel sequence recommendation from social media. The first paper is “Partial Copy Detection in Videos: A Benchmark and An Evaluation of Popular Metho...
متن کاملGuest Editorial: Big Scholar Data Discovery and Collaboration
THE last part of the special issue includes two papers—an interesting empirical study using the very large scholarly dataset described in the solicitation of this special issue, and a survey paper serving as an outlook of the field. In the paper “The Habits of Highly Effective Researchers: An Empirical Study” by Datta, Basuchowdhuri, Acharya and Majumder, the authors attempted to discern some c...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Vision
سال: 2016
ISSN: 0920-5691,1573-1405
DOI: 10.1007/s11263-016-0914-5