Element Detection relying on Information Retrieval Techniques applied to Laser Spectroscopy
Amato Giuseppe, Legnaioli Stefano, Lorenzetti Giulia, Palleschi Vincenzo, Pardini Lorenzo, Rabitti Fausto
LIBS Laser spectroscopy information retrieval
In this paper, we propose a technique for automatic element detection from Laser Induced Breakdown Spectroscopy (LIBS) spectra. The presented approach uses a technique derived from information retrieval and, more specifically, from the emph{Vector Space Model}, to compute the similarity between spectra of elements and samples. These spectra, obtained by LIBS methods, can be represented as sequences of peaks of light emissions of specific wavelengths and intensities. In text retrieval, vectors are built using terms of the vocabulary and weight assessing the relevance of terms in documents or queries. In our case, peaks play the role of terms, elements that of documents, and samples that of queries. We will discuss how to define vectors, weights, and similarity between spectra. Experiments prove the validity of the method.
Source: SISAP 2011 - Fourth International Conference on SImilarity Search and APplications, pp. 89–95, Lipari, Italy, 30 Giugno - 1 Luglio 2011
Publisher: ACM Press, New York, USA
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@inproceedings{oai:it.cnr:prodotti:206352,
title = {Element Detection relying on Information Retrieval Techniques applied to Laser Spectroscopy},
author = {Amato Giuseppe and Legnaioli Stefano and Lorenzetti Giulia and Palleschi Vincenzo and Pardini Lorenzo and Rabitti Fausto},
publisher = {ACM Press, New York, USA},
booktitle = {SISAP 2011 - Fourth International Conference on SImilarity Search and APplications, pp. 89–95, Lipari, Italy, 30 Giugno - 1 Luglio 2011},
year = {2011}
}
0000-0003-0171-4315