Results 191 to 200 of about 6,701,261 (238)

Clustering of multi-source data

3rd IET International Conference on Intelligent Environments (IE 07), 2007
Due to the advent of pervasive and distributed computing, the shift in data processing paradigms is quite visible in many applications (e.g., communication, industrial control, public administrations, geographically distributed business, etc.). The switch from centralized processing paradigm to the local processing paradigm is becoming a necessity due ...
openaire   +1 more source

Querying multi-source heterogeneous fuzzy spatiotemporal data

Journal of Intelligent & Fuzzy Systems, 2021
With the rapid development of the environmental, meteorological and marine data management, fuzzy spatiotemporal data has received considerable attention. Even though some achievements in querying aspect have been made, there are still some unsolved problems.
Bai, Luyi, Li, Nan, Liu, Lishuang, Hao, Xuesong   +3 more
openaire   +1 more source

Multi-source data retrieval in IoT via named data networking

Proceedings of the 1st ACM Conference on Information-Centric Networking, 2014
The new era of Internet of Things (IoT) is driving the revolution in computing and communication technologies spanning every aspect of our lives. Thanks to its innovative concepts, such as named content, name-based routing and in-network caching, Named Data Networking (NDN) appears as a key enabling paradigm for IoT.
Amadeo M, Campolo C, MOLINARO, Antonella
openaire   +2 more sources

A General Multi-Source Data Fusion Framework

Proceedings of the 2019 11th International Conference on Machine Learning and Computing, 2019
With the development of the Internet, the increase of information sources and speed of information release and transmission have led to a sharp increase in the amount of information. To enable users finding more accurate and reliable information in the large heterogeneous multi-source data, data fusion technology becomes more and more important.
Weiming Liu, Chen Zhang, Bin Yu, Yitong Li   +3 more
openaire   +1 more source

Study on Traffic Multi-Source Data Fusion

International Journal of Cognitive Informatics and Natural Intelligence, 2019
In order to alleviate urban traffic congestion, it is necessary to obtain roadway network traffic flow parameters to estimate the traffic conditions. Single-detector data may not be sufficient to obtain a comprehensive, effective, accurate and high-quality traffic flow data.
Suping Liu, Dongbo Zhang, Jialin Li
openaire   +1 more source

A Multi-source Sensor Data Fusion System

Twenty-Second Asilomar Conference on Signals, Systems and Computers, 2005
The Prototype Information Correlation Exploitation System (PICES) is an integrated tracking, data correlation, and multi-frequency multi-sensor data fusion system that automatically generates scene hypotheses (possibilities due to information ambiguities) and ranks them on the basis of all information available to the system at a given time. This paper
J.J. Fitchek, J.P. Lee, D.F. Herring
openaire   +1 more source

Personalized Recommender Systems with Multi-source Data

2020
Pervasive applications of personalized recommendation models aim to seek a targeted advertising strategy for business development and to provide customers with personalized suggestions for products or services based on their personal experience. Conventional approaches to recommender systems, such as Collaborative Filtering (CF), use direct user ...
Yili Wang, Tong Wu, Fei Ma, Shengxin Zhu
openaire   +1 more source

A spatiotemporal deep learning approach for citywide short-term crash risk prediction with multi-source data.

Accident Analysis and Prevention, 2019
The primary objective of this study is to investigate how the deep learning approach contributes to citywide short-term crash risk prediction by leveraging multi-source datasets.
Jie Bao, Pan Liu, S. Ukkusuri
semanticscholar   +1 more source

A multi-source data face recognition algorithm

2013 8th International Conference on Computer Science & Education, 2013
The recognition rate decrease rapidly when expression changes or an angle exits in face recognition.In order to solve this problem, we proposed a multi-source data recognition algorithm based on two-dimensional principal component analysis (2DPCA). By extracting the feature of the front, left side and right side face, we get three principal component ...
null Ye Jihua, null Xia Guomiao, null Hu Dan   +2 more
openaire   +1 more source

Editorial deep multi-source data analysis

Pattern Recognition Letters, 2021
Shichao Zhang, Qing Xie, Yanrong Guo
openaire   +1 more source