In pattern recognition systems, data fusion is an important issue and evidence theory is one such method that has been successful. Many researchers have proposed different rules fo...
—Data fusion is the process of integrating multiple sources of information such that their combination yields better results than if the data sources are used individually. This ...
Data fusion and multicue data matching are fundamental tasks of high-dimensional data analysis. In this paper, we apply the recently introduced diffusion framework to address these...
Measuring effectiveness of information retrieval (IR) systems is essential for research and development and for monitoring search quality in dynamic environments. In this study, w...
The energy scaling laws of multihop data fusion networks for distributed inference are considered. The fusion network consists of randomly located sensors independently distributed...
Animashree Anandkumar, Joseph E. Yukich, Lang Tong...
: In information retrieval, data fusion is a technique for combining the outputs of more than one retrieval strategy which rank documents for retrieval. One of the observations oft...
Although the application of data fusion in information retrieval has yielded good results in the majority of the cases, it has been noticed that its achievement is dependent on the...
This paper describes an approach for using several levels of data fusion in the domain of autonomous off-road navigation. We are focusing on outdoor obstacle detection, and we pre...
In data fusion, score normalization is a step to make scores, which are obtained from different component systems for all documents, comparable to each other. It is an indispensabl...
Data fusion on the Web refers to the merging, into a unified single list, of the ranked document lists, which are retrieved in response to a user query by more than one Web search...