Standard

The Application of Clustering Techniques to Group Archaeological Artifacts. / Mikhailova, N.; Mikhailova, E.; Grafeeva, N.

New Knowledge in Information Systems and Technologies - Volume 1. ed. / Hojjat Adeli; Luís Paulo Reis; Álvaro Rocha; Sandra Costanzo. Springer Nature, 2019. p. 50-57 (Advances in Intelligent Systems and Computing; Vol. 930).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Mikhailova, N, Mikhailova, E & Grafeeva, N 2019, The Application of Clustering Techniques to Group Archaeological Artifacts. in H Adeli, LP Reis, Á Rocha & S Costanzo (eds), New Knowledge in Information Systems and Technologies - Volume 1. Advances in Intelligent Systems and Computing, vol. 930, Springer Nature, pp. 50-57, World Conference on Information Systems and Technologies, WorldCIST 2019, Galicia, Spain, 16/04/19. https://doi.org/10.1007/978-3-030-16181-1_5

APA

Mikhailova, N., Mikhailova, E., & Grafeeva, N. (2019). The Application of Clustering Techniques to Group Archaeological Artifacts. In H. Adeli, L. P. Reis, Á. Rocha, & S. Costanzo (Eds.), New Knowledge in Information Systems and Technologies - Volume 1 (pp. 50-57). (Advances in Intelligent Systems and Computing; Vol. 930). Springer Nature. https://doi.org/10.1007/978-3-030-16181-1_5

Vancouver

Mikhailova N, Mikhailova E, Grafeeva N. The Application of Clustering Techniques to Group Archaeological Artifacts. In Adeli H, Reis LP, Rocha Á, Costanzo S, editors, New Knowledge in Information Systems and Technologies - Volume 1. Springer Nature. 2019. p. 50-57. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-030-16181-1_5

Author

Mikhailova, N. ; Mikhailova, E. ; Grafeeva, N. / The Application of Clustering Techniques to Group Archaeological Artifacts. New Knowledge in Information Systems and Technologies - Volume 1. editor / Hojjat Adeli ; Luís Paulo Reis ; Álvaro Rocha ; Sandra Costanzo. Springer Nature, 2019. pp. 50-57 (Advances in Intelligent Systems and Computing).

BibTeX

@inproceedings{9d0972d446d24df884f81d0075465526,
title = "The Application of Clustering Techniques to Group Archaeological Artifacts",
abstract = "Modern methods of data analysis are rarely used in archaeology. Meanwhile, it is archaeology that opens up impressive opportunities for various interdisciplinary studies at the junction of archaeology, chemistry, physics and mathematics. XRF analysis, which has long been used to determine the qualitative and quantitative composition of discovered archaeological artifacts, among other things, provides arrays of digital information that can be used by machine learning methods for more accurate clustering or classification of artifacts. This is especially true for artifacts that are presented in the form of fragments of ancient ceramic amphorae or glass vessels. Such fragments, as a rule, represent the mass of the fragments mixed among themselves. There is a need to divide them into groups and then restore them as a single artifact from the detected fragments of one group. This paper presents a comparative analysis of the application of different clustering methods to combine artifacts into groups with similar properties.",
keywords = "Archaeological artifacts, Ceramics, Chemical composition, Clustering, Glass, X-ray fluorescence analysis (XRF analysis)",
author = "N. Mikhailova and E. Mikhailova and N. Grafeeva",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-16181-1_5",
language = "English",
isbn = "9783030161804",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Nature",
pages = "50--57",
editor = "Hojjat Adeli and Reis, {Lu{\'i}s Paulo} and {\'A}lvaro Rocha and Sandra Costanzo",
booktitle = "New Knowledge in Information Systems and Technologies - Volume 1",
address = "Germany",
note = "World Conference on Information Systems and Technologies, WorldCIST 2019 ; Conference date: 16-04-2019 Through 19-04-2019",

}

RIS

TY - GEN

T1 - The Application of Clustering Techniques to Group Archaeological Artifacts

AU - Mikhailova, N.

AU - Mikhailova, E.

AU - Grafeeva, N.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Modern methods of data analysis are rarely used in archaeology. Meanwhile, it is archaeology that opens up impressive opportunities for various interdisciplinary studies at the junction of archaeology, chemistry, physics and mathematics. XRF analysis, which has long been used to determine the qualitative and quantitative composition of discovered archaeological artifacts, among other things, provides arrays of digital information that can be used by machine learning methods for more accurate clustering or classification of artifacts. This is especially true for artifacts that are presented in the form of fragments of ancient ceramic amphorae or glass vessels. Such fragments, as a rule, represent the mass of the fragments mixed among themselves. There is a need to divide them into groups and then restore them as a single artifact from the detected fragments of one group. This paper presents a comparative analysis of the application of different clustering methods to combine artifacts into groups with similar properties.

AB - Modern methods of data analysis are rarely used in archaeology. Meanwhile, it is archaeology that opens up impressive opportunities for various interdisciplinary studies at the junction of archaeology, chemistry, physics and mathematics. XRF analysis, which has long been used to determine the qualitative and quantitative composition of discovered archaeological artifacts, among other things, provides arrays of digital information that can be used by machine learning methods for more accurate clustering or classification of artifacts. This is especially true for artifacts that are presented in the form of fragments of ancient ceramic amphorae or glass vessels. Such fragments, as a rule, represent the mass of the fragments mixed among themselves. There is a need to divide them into groups and then restore them as a single artifact from the detected fragments of one group. This paper presents a comparative analysis of the application of different clustering methods to combine artifacts into groups with similar properties.

KW - Archaeological artifacts

KW - Ceramics

KW - Chemical composition

KW - Clustering

KW - Glass

KW - X-ray fluorescence analysis (XRF analysis)

UR - http://www.scopus.com/inward/record.url?scp=85064866454&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/application-clustering-techniques-group-archaeological-artifacts

U2 - 10.1007/978-3-030-16181-1_5

DO - 10.1007/978-3-030-16181-1_5

M3 - Conference contribution

AN - SCOPUS:85064866454

SN - 9783030161804

T3 - Advances in Intelligent Systems and Computing

SP - 50

EP - 57

BT - New Knowledge in Information Systems and Technologies - Volume 1

A2 - Adeli, Hojjat

A2 - Reis, Luís Paulo

A2 - Rocha, Álvaro

A2 - Costanzo, Sandra

PB - Springer Nature

T2 - World Conference on Information Systems and Technologies, WorldCIST 2019

Y2 - 16 April 2019 through 19 April 2019

ER -

ID: 42330961