Link-based data structures, such as linked lists and binary search trees, have many well-known rearrangement steps allowing for efficient implementations of insertion, deletion, and other operations. We describe a rearrangement primitive designed for link-based, heap-ordered priority queues in the comparison model, such as those similar to Fibonacci heaps or binomial heaps. In its most basic form, the primitive rearranges a collection of heap-ordered perfect binary trees. Doing so offers a data structure control on the number of trees involved in such a collection, in particular keeping this number logarithmic in the number of elements. The rearrangement step is free from an amortized complexity standpoint (using an appropriate potential function).

Despite the huge amount of computer data that exists today, the task of sharing information between organizations is still tackled largely on a case-by-case basis. The M Language is a data language that improves data sharing and interoperability by building a platform on top of XML and a semantic dictionary. Because the M Language is specifically designed for real-world data applications, it gives rise to several unique problems in natural language processing. I approach the problem of understanding unknown words by devising a novel heuristic for word decomposition called "probabilistic chunking," which achieves a 70% success rate in word syllabification and has potential applications in automatically decomposing words into morphemes. I also create algorithms which use probabilistic chunking to syllabify unknown words and thereby guess their parts of speech and semantic relations. This work contributes valuable methods to the areas of natural language processing and automatic data processing. Thesis Supervisor: David L. Brock Title: Principal Research Scientist, Lab for Manufacturing and Productivity