Summary
We discuss two simple strategies for constructing binary search trees: “Place the most frequently occurring name at the root of the tree, then proceed similary on the subtrees “and” choose the root so as to equalize the total weight of the left and right subtrees as much as possible, then proceed similarly on the subtres.” While the former rule may yield extremely inefficient search trees, the latter rule always produces nearly optimal trees.
Similar content being viewed by others
References
Fredman, M. L.: Two applications of a probabilistic search technique: Sorting X + Y and building balanced search trees. 7th ACM Symposium on Theory of Computing, Albuquerque, 1975
Hu, T. C., Tan, K. C.: Least upper bound on the cost of optimum binary search trees. Acta Informatica 1, 307–310 (1972)
Kameda, T., Weihrauch, K.: Einführung in die Kodierungstheorie I. BI Skripten zur Informatik, Vol. 7. Mannheim: Bibliographisches Institut 1971
Knuth, D. E.: Optimum binary search trees. Acta Informatica 1, 14–25 (1971)
Knuth, D. E.: The art of computer programming, Vol. 3. Reading (Mass.): Addison-Wesley 1973
Rissanen, J.: Bounds for weighted balanced trees. IBM J. Res. Develop. March 1973, 101–105
Walker, W. A., Gotlieb, C. C.: A top-down algorithm for constructing nearly optimal lexicographical trees, in Graph theory and Computing. New York: Academic Press 1972
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Mehlhorn, K. Nearly optimal binary search trees. Acta Informatica 5, 287–295 (1975). https://doi.org/10.1007/BF00264563
Received:
Issue Date:
DOI: https://doi.org/10.1007/BF00264563