Main Focus: Computational Linguistics
Computational
linguistics has applications ranging from machine translation [129] and
declarative query languages [128] to talking robots.
Computational linguistics is also used to automate some of the work that
linguists did manually, such as building online searchable dictionaries
and data mining those dictionaries to find possible cognate words, and
automatically generate Swadesh
lists. The data mining can also estimate
the degree of divergence between any pair of languages and use those estimates
to automatically generate language family trees.
Many linguists try to decipher ancient scripts. Decipherment involves
identifying the phonetic values of script symbols. That is a difficult problem
because if we need to assign to each of n signs one of n
different phonetic values, then there are n!
possibilities. Clearly, the search space needs
to be pruned in some way. Bilingual texts with proper names can help pruning
the search space. In the absence of bilingual texts, Michael Ventris
used an alternative pruning method to decipher the Linear B script. The
alternative method was matching the Linear B signs with the Cypriot Syllabary
signs, whose phonetic values were already known. Matching two sets of signs can
be done manually, as Ventris did, or by a computer vision algorithm,
as we did [2, 16, 23, 33] in matching the Linear A script, the Carian Alphabet, and
the Old
Hungarian Alphabet. The matches suggested phonetic values
for Linear A and led to the decipherment of many Linear A texts [26]. The
translation work still continues as there are over 1300 Linear A and over 400
related Cretan
Hieroglyphic texts and the Phaistos Disk [4, 32]. The translations help
reveal previously unknown aspects of the Minoan civilization.
Data mining is applied to archaeogenetics [10, 15], art motifs [18], vowel
harmony [11], regular sound changes [7, 12, 19], toponyms [22] and weights [8].
These results help identify the origins of the Minoans and the language family
to which the Minoan language belongs. The AIDA (Ancient Inscription
Database and Analytics) system [17] provides an online, searchable
Minoan inscriptions database for scholars. Recently, we also developed a method
to identify allographs in undeciphered scripts with a focus on the Indus Valley
Script [9], which has puzzled researchers for over a century.
Research News
'Mysterious'
inscription on ancient sphinx is deciphered, Miami Herald
Mysterious
inscription on ancient bronze sphinx statue is deciphered, Archaeology News
‘Mysterious’
inscription on ancient Dacia sphinx is deciphered, Arkeonews
Une
mystérieuse inscription sur un ancien sphinx de la région de Dacie enfin
déchiffrée, GEO
Mysterious
Greek Inscription on Ancient Sphinx Deciphered, Greek Reporter
Studioso
usa specchio leonardesco e traduce il mistero della Sfinge, adorata da un
gruppo di legionari romani nel III secolo, Stile Arte
Revesz
decodes ancient sphinx’s mysterious message, Nebraska Today
Could
AI Language Models Like ChatGPT Unlock Mysterious Ancient Texts?, Discover
Magazine
Origins of the Ancient
Minoans | DNA, SAMA interview
Symmetry in Ancient
Scripts, ISSI plenary invited talk
Origin of European River
and Mountain Names, ADBIS keynote presentation
Linear
A: Early Cretan Writing System, ThoughtCo
Medium,
OMNIKA library,
RovasInfo
Selected Publications
7.
P. Z. Revesz, Sumerian-Ugric protowords and regular sound changes,
Appendix to: S. Parpola, Etymological Dictionary of the Sumerian Language,
vol. 3, Eisenbrauns, pp. 390-415, 2022.
27. P. Z. Revesz, A
translation of the Arkalochori Axe and the Malia Altar Stone,
WSEAS Transactions on Information Science and Applications, 14, 124-133,
2017.
44. P.
Z. Revesz, and D. Singh, Efficient
and robust constraint automaton-based genome map assembly,
Proc. 4th International C* Conference on Computer Science and Software Engrineering,,
ACM Press, 9, 1-9, 2014.
49. H.
Yue, and P. Z. Revesz, TVICS: An
efficient traffic video information converting system,
19th International Symposium on Temporal Representation and Reasoning,
IEEE Press, pp. 141-148, 2012.
52. V.
Santosh, M. Griep, and P. Z. Revesz, Protein structure-based method for identifying horizontal gene
transfer,
Proc. 1st International C* Conference on Computer Science and Software Engrineering,,
ACM Press, pp. 9-16, 2011.
53. A.
Ngo, and P. Z. Revesz, Efficient
traffic crash and snow complaint GIS system,
12th International Conference on Digital Government Research, ACM Press,
pp. 235-244, 2011.
65. P.
Z. Revesz, and T. Triplet, Reclassification
of linearly classified data using constraint databases,
12th East-European Conference on Advances in Databases and Information
Systems, Springer LNCS 5207, pp. 231-245, Pori, Finland, 2008.
66. S.
Haesevoets, B. Kuijpers, and P. Z. Revesz, Efficient affine-invariant similarity retrieval,
2nd International Conference on Geometric Modeling and Imaging, IEEE
Press, pp. 99-108, 2007.
67. S.
Anderson, and P. Z. Revesz, CDB-PV:
A constraint database-based program verifier,
7th Int. Symp. on Abstraction, Reformulation and Approximation, Springer
LNCS 4612, pp. 35-49, 2007.
68. P.
Z. Revesz, The constraint database
approach to software verification,
8th Int. Conf. on Verification, Model Checking and Abstract
Interpretationon, Springer LNCS 4349, pp. 329-345, 2007.
70. K.
Mercier, M. Baran, V. Ramanathan, P. Z. Revesz, R. Xiao, G. Montelione, R.
Powers, FAST-NMR:
Functional annotation screening technology using NMR,
Journal of the American Chemical Society, 128 (47), 15292-99, 2006.
73. F.
Geerts, P. Z. Revesz, and J. Van den Bussche, On-line maintenance of simplified weighted graphs for efficient
distance queries,
ACM SIGSPATIAL International Conf. on Advances in Geographic Information
Systems, ACM Press, pp. 203-210, 2006.
74. J.
Gao, and P. Z. Revesz, Visualization
of temporal-oriented data sets,
1st International Conference on Geometric Modeling and Imaging, IEEE
Press, pp. 57-62, 2006.
77. S.
Anderson and P. Z. Revesz, Verifying
the incorrectness of programs and automata,
6th Int. Symp. on Abstraction, Reformulation and Approximation, Springer
LNCS 3607, pp. 1-13, 2005.
78. J.
Gao, and P. Z. Revesz, Adaptive
spatio-temporal interpolation methods,
8th Joint Conference on Information Sciences, Curran Associates, pp.
1677-90, 2005.
84. S.
Wu and P. Z. Revesz, DOAS: A drought
online analysis system with constraint databases,
5th International Conference on Digital Government Research, Digital
Government Society Press, pp. 417-418, 2004.
85. Y.
Chen and P. Z. Revesz, Max-Count
aggregation estimation for moving points,
11th International Symposium on Temporal Representation and Reasoning,
IEEE Press, pp. 103-108, 2004.
86. P.
Z. Revesz and S. Wu, Visualization of
recursively defined concepts,
8th International Conference on Information Visualisation, IEEE Press,
pp. 613-621, 2004.
89. L.
Li, and P. Z. Revesz, The
relationship among GIS-oriented spatiotemporal databases,
4th International Conference on Digital Government Research, Digital
Government Society Press, pp. 375-378, 2003.
91. Y.
Chen, and P. Z. Revesz, Querying
spatiotemporal XML using DataFox,
IEEE International Conference on Web Intelligence, IEEE Press, pp.
301-309, October 2003.
92. Y.
Chen and P. Z. Revesz, Efficient
aggregation over moving objects,
10th International Symposium on Temporal Representation and Reasoning,
IEEE Press, 118-127, July 2003.
93. P.
Z. Revesz, A retrosceptive on
constraint databases,
In: PCK50 - Principles of Computing and Knowledge, Paris C. Kanellakis
Memorial Workshop, San Diego, CA, June 2003.
96. L.
Li, and P. Z. Revesz, A
comparison of spatio-temporal interpolation methods,
2nd International Conference on Geographic Information Science, Springer
LNCS 2478, 145-160, Sept. 2002.
99. P.
Z. Revesz, R. Chen, M. Ouyang, Approximate
query evaluation using linear constraint databases,
8th International Symposium on Temporal Representation and Reasoning,
IEEE Press, 170-175, June 2001.
100. Y.
Deng and P. Z. Revesz, Spatial
and topological data models,
In: Information Modeling in the New Millennium, M. Rossi, K. Siau, eds.,
IGI Publishing, pp. 345-59, 2001.
102. M.
Cai, and P. Z. Revesz, Parametric
R-tree: An index structure for moving objects,
10th International Conference on Management of Data, McGraw Hill, pp.
57-64, Pune, India, December 2000.
103. M.
Ouyang, and P. Z. Revesz, Algorithms
for cartogram animation,
International Database Engineering and Applications Symposium, IEEE
Press, pp. 231-235, Yokohama, Japan, Sept. 2000.
104. R.
Chen, M. Ouyang, P. Z. Revesz, Approximating
data in constraint databases,
4th Int. Symp. on Abstraction, Reformulation and Approximation, Springer
LNAI 1864, 124-143, July 2000.
105. P.
Z. Revesz, Reformulation and
approximation in model checking,
4th Int. Symp. on Abstraction, Reformulation and Approximation, Springer
LNAI 1864, 202-218, July 2000.
106. P.
Z. Revesz, R. Chen, P. Kanjamala, Y. Li, Y. Liu, and Y. Wang The MLPQ/GIS constraint database
system,
ACM-SIGMOD International Conference on Management of Data (SIGMOD), ACM
Press, Dallas, Texas, USA, May 2000.
107. P.
Z. Revesz, Datalog
and constraints,
In: Constraint Databases, G. Kuper, L. Libkin, J. Paredaens, eds.,
Springer, 155-170, 2000.
108. P.
Z. Revesz, The DISCO system,
In: Constraint Databases, G. Kuper, L. Libkin, J. Paredaens, eds.,
Springer, 383-389, 2000.
110. J.
Chomicki, Y. Liu, and P. Z. Revesz, Animating
spatiotemporal constraint databases,
Workshop on Spatio-Temporal Database Management (STDBM), Springer LNCS
1678, Edinburgh, Scotland, September 1999.
111. P.
Z. Revesz, Datalog programs with
difference constraints,
Seventh International Workshop on Deductive Databases and Logic Programming,
Japanese Computer Sociey Press, 69-76, Tokyo, Japan, Sept. 1999.
112. J.
Chomicki, and P. Z. Revesz, A
Geometric Framework for Specifying Spatiotemporal Objects,
Sixth International Conf. on Temporal Representation and Reasoning (TIME),
IEEE Press, 41-46, Orlando, Florida, May 1999.
115. P.
Z. Revesz, Constraint databases: A
survey,
In: Semantics in Databases, L. Libkin and B. Thalheim, eds., Springer
LNCS 1358, 209-246, 1998.
116. P.
Z. Revesz, Safe Datalog queries with
linear constraints,
4th International Conference on Principles and Practice of Constraint
Programming (CP), Springer LNCS 1520, 355-369, 1998.
117. P.
Kanjamala, P. Z. Revesz, and Y. Wang, MLPQ/GIS: A geographic information system using linear
constraint databases,
9th International Conference on Management of Data (COMAD), McGraw Hill,
389-392, Hyderabad, India, December 1998.
118. P.
Z. Revesz and Y. Li, MLPQ: A
linear constraint database system with aggregate operators,
International Database Engineering and Applications Symposium, IEEE
Press, 132-137, Montreal, Canada, 1997.
120. G. Grahne,
A.O. Mendelzon, P. Z. Revesz, Knowledgebase
transformations,
Journal of Computer and System Sciences, 54 (1), 98-112, 1997.
121. P.
Z. Revesz, On the semantics of
arbitration,
International Journal of Algebra and Computation, 7 (2), 133-160, 1997.
122. P.
Z. Revesz, Problem solving in the
DISCO constraint database system,
2nd International Workshop on Constraint Database Systems, Springer LNCS
1191, 302-315, Delphi, Greece, 1997.
125. A.
Benczur, A.B. Novak, P. Z. Revesz, Classical and weighted knowledgebase transformations,
Computers and Mathematics with Applications, 32 (5), 85-98, 1996.
126. J.
Byon, and P. Z. Revesz, DISCO: A
constraint database system with sets,
Workshop on Constraint Databases and Applications, Springer LNCS 1034,
68-83, 1995.
127. K.
L. Lu, and P. Z. Revesz, The
capacity of matcher neural networks,
In: Intelligent Engineering Systems Through Artificial Neural Networks,
C. Dagli, ed., ASME Press, 15-20, 1995.
128. P.
C. Kanellakis, G. M. Kuper, P. Z. Revesz, Constraint query languages,
Journal of Computer and System Sciences, 51 (1), 26-52, 1995.
129. P.
Z. Revesz and R. K. Veera, A
sign-to-speech translation system using matcher neural networks,
In: Intelligent Engineering Systems Through Artificial Neural Networks,
C. Dagli, ed., ASME Press, 369-374, 1993.
Selected Dissertations Supervised