Welcome to the UCR Computational Anthropology Site
This page is designed to report progress on our NSF funded project: Tools to Mine and Index Trajectories of Physical Artifacts. IIS Division of Information & Intelligent Systems 0803410 (2008-11). We gratefully acknowledge the financial support of NSF, and the moral support of our program director. |
The PI is Eamonn Keogh, the Co-PI's are Vassilis Tsotras, (UCR CS) and Sang-Hee Lee (UCR Anthropology)
Our proposals abstract:
The project proposes to develop computational methods and tools for the discovery of spatio-temporal patterns in the distribution and historical development of physical artifacts important to anthropology including the development of a shape recognition system that allows researchers to compare numerous projectile points and petroglyphs according to several criteria. This will involve creation of a set of definitions/ data representations/predicates/algorithms and intuitive and usable software tools to enable the study of the spatio-temporal spread of physical objects. The proposal uses innovative technology to apply to questions central to archaeology. but which also has broad applicability to research in other, diverse domains.
Publications:
Directly Related:
- Qiang Zhu and Eamonn Keogh (2010) Using CAPTCHAs to Index Cultural Artifacts. The Ninth International Symposium on Intelligent Data Analysis. (IDA)
- Xiaoyue Wang, Lexiang Ye, Eamonn Keogh and Christian Shelton. Annotating Historical Archives of Images (2009). International Journal of Digital Library Systems (IJDLS).
- Lexiang Ye and Eamonn Keogh (2009) Time Series Shapelets: A New Primitive for Data Mining. SIGKDD 2009
- Qiang Zhu, Xiaoyue Wang, Eamonn Keogh, Sang-Hee Lee (2009). Augmenting the Generalized Hough Transform to Enable the Mining of Petroglyphs. SIGKDD 2009
- Qiang Zhu, Xiaoyue Wang, Taryn Rampley, Eamonn Keogh and Sang-Hee Lee (2009) Towards Indexing and Data Mining all the Worlds Rock Art. In the 37th Annual International Conference on Computer Applications and Quantitative Methods in Archeology (CAA 2009)
- Taryn Rampley, Eamonn Keogh, Lexiang Ye and Sang-Hee Le (2009) Automatic Construction of Typologies for Massive Collections of Projectile Points and other Cultural Artifacts. In the 37th Annual International Conference on Computer Applications and Quantitative Methods in Archeology (CAA 2009)
- Rampley, Taryn T., Sang-Hee Lee, Lexiang Ye, and Eamonn Keogh (2010) The Spread of Clovis: the application of shape similarity indexing to understanding population dynamics. Paper presented at the 75th Anniversary Meeting of the Society for American Archaeology. St. Louis, Missouri. April 14 - 18, 2010
Indirectly Related: These are publications funded by the grant, which are not directly on computational anthropology but are one either spin-off technologies or enabling technologies that can be applied to anthropology.
- Abdullah Mueen, Eamonn Keogh, Qiang Zhu, Sydney Cash, Brandon Westover. Exact Discovery of Time Series Motifs. SIAM International Conference on Data Mining, 2009. (We are using the MK motif discovery algorithm invented here to find motifs in petroglyphs)
- Abdullah Mueen, Eamonn Keogh and Nima Bigdely-Shamlo (2009). Finding Time Series Motifs in Disk-Resident Data. ICDM 2009.
Tutorials:
Directly Related:
- Eamonn Keogh: Mining Massive Collections of Shapes and Time Series: With Case Studies in Anthropology. ACISS’09. 1 December. Melbourne, Australia
Indirectly Related: These are tutorials funded by the grant, but are not directly on computational anthropology but are part of our broader outreach and service..
- Eamonn Keogh: How to do good research, get it published in SIGKDD and get it cited! SIGKDD 2009. This tutorial does use examples from this grant, in the (15-slide) section on the importance of testing on real data.
- Eamonn Keogh: How to do good database/data mining research, and get it published! ACISS’09. 30 November. Melbourne, Australia
Data:
We plan to release all our data, in general the data will be made available within 6-months of being used in a publication. However if you have a pressing need, just ask.
African Projectile Points: This dataset consists of images of 186 points, about 4000 to 6000 years old, found in Sahara Desert. We can send you the data on a free CD-Rom. In addition, the physical objects are in our personal collection, so we can arrange for you to examine them in person (just ask). Leaf shape; serrated edge: 44 objects. Lanceolate to triangular; square to contracting stem: 77 objects. Triangular; concave base to basal notching: 21 objects. Triangular; barbed: 14 objects. Class Misc - this was a miscellaneous group: 30 objects.
Notes:
- Can human computation meaningfully extract data from petroglyph images? Here is a simply sanity check.
Funded Students: To date, the following students have been partly or fully funded by this grant.
Part Time
Data Donors: To date, the following people have donated data: