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BY-NC-ND 3.0 license Open Access Published by De Gruyter Open Access March 21, 2015

Extracting Information from Archaeological Texts

  • Keith W. Kintigh
From the journal Open Archaeology

Abstract

To address archaeology’s most pressing substantive challenges, researchers must discover, access, and extract information contained in the reports and articles that codify so much of archaeology’s knowledge. These efforts will require application of existing and emerging natural language processing technologies to extensive digital corpora. Automated classification can enable development of metadata needed for the discovery of relevant documents. Although it is even more technically challenging, automated extraction of and reasoning with information from texts can provide urgently needed access to contextualized information within documents. Effective automated translation is needed for scholars to benefit from research published in other languages.

References

[1] Kintigh, K.W., Altschul, J.H., Beaudry, M.C., Drennan, R.D., Kinzig, A.P., Kohler, T.A., et al., Grand challenges for archaeology, American Antiquity 2014, 79(1), 5-24 10.7183/0002-7316.79.1.5Search in Google Scholar

[2] Kintigh, K.W., Altschul, J.H., Beaudry, M.C., Drennan, R.D., Kinzig, A.P., Kohler, T.A., et al., Grand challenges for archaeology, Proceedings of the National Academy of Sciences, 2014, 111(3), 879-88 10.1073/pnas.1324000111Search in Google Scholar

[3] Departmental Consulting Archeologist, The Secretary’s report to Congress on the Federal Archeological Program, comparable SRC data 1985-2012, by year. Archeology Program, National Park Service, Washington, DC, http://www.nps. gov/archeology/SRC/data.htm, 2015 Search in Google Scholar

[4] Altschul, J. H., Patterson, T.C., Trends in employment and training in American archaeology. In: Ashmore, W., Lippert, D., Mills, B.J. (Eds.), Voices in American archaeology, Society for American Archaeology, Washington DC, 2010 Search in Google Scholar

[5] Archaeology Data Service, Center for Digital Antiquity, Caring for digital data in archaeology: a guide to good practice. Oxbow Books, Oxford, UK, 2013 http://guides.archaeologydataservice.ac.uk/ Search in Google Scholar

[6] Michel, J., Shen, Y.K., Aiden, A.P., Veres, A., Gray, M.K., the Google Books Team, et al., Quantitative analysis of culture using millions of digitized books, Science, 331, 176-1812, 2011, DOI: 10.1126/science.1199644 10.1126/science.1199644Search in Google Scholar

[7] Richards, J., Tudhope, D., Vlachidis, A., Text Mining in archaeology: extracting information from archaeological reports, In: Barceló, J.A., Bogdanovic, I., (Eds.), Mathematics in archaeology, Science Publishers, Boca Raton, Florida, (in press) Search in Google Scholar

[8] Jeffrey, S., Richards, J.D., Ciravegna, F., Waller, S., Chapman, S., Zhang, Z., The Archaeotools project: faceted classification and natural language processing in an archaeological context. In: Coveney P., (Ed), Crossing boundaries: computational science, e-Science and global e-infrastructures, Philosophical Transactions of the Royal Society A, 2009, 367, 2507-2519. Search in Google Scholar

[9] Tudhope, D., May, K., Binding, C., Vlachidis, A., Connecting archaeological data and grey literature via semantic cross search, Internet Archaeology 2011, 30, DOI: 10.11141/ia.30.5 10.11141/ia.30.5Search in Google Scholar

[10] Baral, C., Chancellor, K., Tran, N., Tran, N.L., Joy, A, Berens, M., A knowledge based approach for representing and reasoning about signaling networks, Bioinformatics 2004, 20, no. suppl 1 (2004), i15-i22. 10.1093/bioinformatics/bth918Search in Google Scholar

[11] Tran, N., Baral, C., Nagaraj, V.J., Joshi, L., Knowledge-based framework for hypothesis formation in biochemical networks, Bioinformatics, 2005, 21, supplement 2, ii213–219. 10.1093/bioinformatics/bti1134Search in Google Scholar

[12] Howell, T.L., The archaeology and ethnohistory of Oak Wash, Zuni Indian Reservation, New Mexico, Zuni Cultural Resource Enterprise Report, 2000, 644, Zuni, New Mexico Search in Google Scholar

[13] Clark, T.C., Assessing room function using unmodified faunal bone: a case study from east-central Arizona, Kiva, 1998, 64(1), 27–51. 10.1080/00231940.1998.11758367Search in Google Scholar

[14] IBM What is Watson? 2014 http://www.ibm.com/smarterplanet/us/en/ibmwatson/what-is-watson.html Search in Google Scholar

Received: 2014-12-19
Accepted: 2015-2-11
Published Online: 2015-3-21

© 2015 Keith W. Kintigh

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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