Results 11 to 20 of about 898,820 (259)
From data fusion to knowledge fusion [PDF]
Proceedings of the VLDB Endowment, 2014 The task of data fusion is to identify the true values of data items ( e.g. , the true date of birth for Tom Cruise ) among multiple observed values drawn from different sources ( e.g. , Web sites) of varying (and unknown) reliability.
Xin Luna Dong +6 more
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Proceedings of a workshop on held at Baltimore, Maryland October 13-15, 1998 -, 1996 Information retrieval researchers have long appreciated the value of combining, or fusing, multiple retrieval systems' relevance scores for a set of documents to improve retrieval performance. However, it is only recently that researchers have begun to consider adjusting the score fusion method to the user's topic and initial results.
Ted Diamond, Elizabeth D. Liddv
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Data fusion and data grafting [PDF]
Computational Statistics & Data Analysis, 2002 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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IEEE Journal of Selected Topics in Signal Processing, 2015 We present structured data fusion (SDF) as a framework for the rapid prototyping of knowledge discovery in one or more possibly incomplete data sets. In SDF, each data set—stored as a dense, sparse, or incomplete tensor—is factorized with a matrix or tensor decomposition.
Sorber, Laurent +2 more
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Structure-revealing data fusion [PDF]
BMC Bioinformatics, 2014 Analysis of data from multiple sources has the potential to enhance knowledge discovery by capturing underlying structures, which are, otherwise, difficult to extract. Fusing data from multiple sources has already proved useful in many applications in social network analysis, signal processing and bioinformatics.
Evrim Acar +6 more
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, 2010 We consider the problem of specifying data structures with complex sharing in a manner that is both declarative and results in provably correct code. In our approach, abstract data types are specified using relational algebra and functional dependencies; a novel fuse operation on relational indexes specifies where the underlying physical data structure
Hawkins, Peter +4 more
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Choosing the Best Sensor Fusion Method: A Machine-Learning Approach
Sensors, 2020 Multi-sensor fusion refers to methods used for combining information coming from several sensors (in some cases, different ones) with the aim to make one sensor compensate for the weaknesses of others or to improve the overall accuracy or the reliability
Ramon F. Brena +4 more
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Recreating Lunar Environments by Fusion of Multimodal Data Using Machine Learning Models
Engineering Proceedings, 2022 The latest satellite infrastructure for data processing, transmission and reception can certainly be improved by upgrading tools used to deal with very large amounts of data from every different sensor incorporated within the space missions.
Ana C. Castillo +5 more
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City Data Fusion: Sensor Data Fusion in the Internet of Things
CoRR, 2015 Internet of Things (IoT) has gained substantial attention recently and play a significant role in smart city application deployments. A number of such smart city applications depend on sensor fusion capabilities in the cloud from diverse data sources. We introduce the concept of IoT and present in detail ten different parameters that govern our sensor ...
Meisong Wang +5 more
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Identification of Village Building via Google Earth Images and Supervised Machine Learning Methods
Remote Sensing, 2016 In this study, a method based on supervised machine learning is proposed to identify village buildings from open high-resolution remote sensing images.
Zhiling Guo +5 more
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