scispace - formally typeset
Journal ArticleDOI

Data fusion

Jens Bleiholder, +1 more
- 15 Jan 2009 - 
- Vol. 41, Iss: 1, pp 1
TLDR
This article places data fusion into the greater context of data integration, precisely defines the goals of data fusion, namely, complete, concise, and consistent data, and highlights the challenges of data Fusion.
Abstract
The development of the Internet in recent years has made it possible and useful to access many different information systems anywhere in the world to obtain information. While there is much research on the integration of heterogeneous information systems, most commercial systems stop short of the actual integration of available data. Data fusion is the process of fusing multiple records representing the same real-world object into a single, consistent, and clean representation.This article places data fusion into the greater context of data integration, precisely defines the goals of data fusion, namely, complete, concise, and consistent data, and highlights the challenges of data fusion, namely, uncertain and conflicting data values. We give an overview and classification of different ways of fusing data and present several techniques based on standard and advanced operators of the relational algebra and SQL. Finally, the article features a comprehensive survey of data integration systems from academia and industry, showing if and how data fusion is performed in each.

read more

Citations
More filters
Journal ArticleDOI

Linked Data - the story so far

TL;DR: The authors describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked data community as it moves forward.
Journal ArticleDOI

Big Data: A Survey

TL;DR: The background and state-of-the-art of big data are reviewed, including enterprise management, Internet of Things, online social networks, medial applications, collective intelligence, and smart grid, as well as related technologies.
Book

Linked Data: Evolving the Web into a Global Data Space

TL;DR: This Synthesis lecture provides readers with a detailed technical introduction to Linked Data, including coverage of relevant aspects of Web architecture, as the basis for application development, research or further study.
Journal ArticleDOI

BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network

TL;DR: An automatic approach to the construction of BabelNet, a very large, wide-coverage multilingual semantic network, key to this approach is the integration of lexicographic and encyclopedic knowledge from WordNet and Wikipedia.
Journal ArticleDOI

A Review of Relational Machine Learning for Knowledge Graphs

TL;DR: This paper provides a review of how statistical models can be “trained” on large knowledge graphs, and then used to predict new facts about the world (which is equivalent to predicting new edges in the graph) and how such statistical models of graphs can be combined with text-based information extraction methods for automatically constructing knowledge graphs from the Web.
References
More filters
Journal ArticleDOI

Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images

TL;DR: The analogy between images and statistical mechanics systems is made and the analogous operation under the posterior distribution yields the maximum a posteriori (MAP) estimate of the image given the degraded observations, creating a highly parallel ``relaxation'' algorithm for MAP estimation.
Journal ArticleDOI

Inference and missing data

Donald B. Rubin
- 01 Dec 1976 - 
TL;DR: In this article, it was shown that ignoring the process that causes missing data when making sampling distribution inferences about the parameter of the data, θ, is generally appropriate if and only if the missing data are missing at random and the observed data are observed at random, and then such inferences are generally conditional on the observed pattern of missing data.
Proceedings ArticleDOI

The unscented Kalman filter for nonlinear estimation

TL;DR: The unscented Kalman filter (UKF) as discussed by the authors was proposed by Julier and Uhlman (1997) for nonlinear control problems, including nonlinear system identification, training of neural networks, and dual estimation.
Book

Principles of geographical information systems

TL;DR: This paper aims to provide a history of fuzzy logic in information handling and geostatistics and some of the techniques used to deal with fuzzy logic problems.
Related Papers (5)
Trending Questions (1)
What is data fusion in entrepreneurship?

The provided paper does not mention data fusion in the context of entrepreneurship. The paper primarily focuses on data fusion in the context of data integration and information systems.