@inproceedings{c468bf3807f9459f9d628dae61b9014f,
title = "Data association and soft data streams",
abstract = "This paper discusses the challenges of and possible methods for data association in the domain of counterinsurgency where {"}soft/linguistic{"} data is an important input data type. An overview of the processing operations from input to construction of fused estimates is described. The design issues that are discussed and require further exploration to yield a workable and efficient association process include developing an input batching logic, finding efficient ways to search between graphs, and the selection of appropriate semantic similarity metrics to associate nodes and arcs. Additionally, the solution to a multi-dimensional assignment problem and graph merging techniques will need to be defined. The application of data association in this type of environment has potential to yield an improved, comprehensive data graph which will aid in reducing search time and provide more accurate results for analysts making real time decisions in the real world.",
keywords = "Batching, Data association, Graph matching, Graph merging, Multi-dimensional assignment problem, Semantic similarity",
author = "Megan Hannigan and Deven McMaster and James Llinas and Kedar Sambhoos",
year = "2010",
doi = "10.1109/icif.2010.5712079",
language = "English",
isbn = "9780982443811",
series = "13th Conference on Information Fusion, Fusion 2010",
publisher = "IEEE Computer Society",
booktitle = "13th Conference on Information Fusion, Fusion 2010",
address = "United States",
}