Improved approximation of the largest common subtree of two unordered trees of bounded height

We present a polynomial time 1.5h-approximation algorithm for the problem of finding the largest common subtree between two rooted, labeled, and unordered trees of height at most h, where a tree S is called a subtree of a tree T if S is obtained from T by deletion of some nodes in T. This result improves the previous 2h-approximation algorithm.     

A REVIEW OF TREE CONVEX SETS TEST

A collection of sets may have some interesting properties which help identify efficient algorithms for constraint satisfaction problems and combinatorial auction problems. One of the properties is tree convexity. A collection S of sets is tree convex if we can find a tree T whose nodes are the union of the sets of S and each set of S is the nodes of a subtree of T . This concept extends that of row convex sets each of which is an interval over a total ordering of the elements of the union of these sets. An interesting problem is to find efficient algorithms to test whether a collection of sets is tree convex. It is not known before if there exists a linear time algorithm for this test. In this paper, we review the materials that are the key to a linear algorithm: hypergraphs, a characterization of tree convex sets and the acyclic hypergraph test algorithm. Some typos in the original paper of the acyclicity test are corrected here. Some experiments show that the linear algorithm is significantly faster than a well‐known existing algorithm.     

A Faster FPT Algorithm for the Maximum Agreement Forest Problem

Given two unrooted, binary trees, T₁ and T₂, leaf labelled bijectively by a set of species L, the Maximum Agreement Forest (MAF) problem asks to find a minimum cardinality collection F = {t₁, ..., t_k} of phylogenetic trees where each element of F is a subtree of both T₁ and T₂, the elements of F are pairwise disjoint, and the leaf labels for the elements of F partition the leaf label set L. We give an efficient fixed-parameter tractable (FPT) algorithm for the MAF problem, significantly improving on an FPT algorithm given in [2]. Whereas the algorithm from [2] has a running time of O(k^3k) + p(|L|), our algorithm runs in time O(4^k · k⁵) + p(|L|), where k bounds the size of the agreement forest and p(·) is a low order polynomial.     

Improved algorithm for the symmetry number problem on trees

The symmetry number of a tree is defined as the number of nodes of the maximum subtree of the tree that exhibits axial symmetry. The best previous algorithm for computing the symmetry number for an unrooted unordered tree is due to [P.P. Mitra, M.A.U. Abedin, M.A. Kashem, Algorithms for solving the symmetry number problem on trees, Inform. Process. Lett. 91 (2004) 163-169] and runs in O(n³) time. In this paper we show an improvement on this time complexity by encoding small trees. Our algorithm runs in time O(n³²(loglogn/logn)).     

Equivalence of Binary and Ternary Algebraic Decision Trees

Two models of algebraic decision trees have been studied. The binary model allows queries of the form ``is p(x ₁ ,... , x _n ) ≤ 0?', while in the ternary model the value of the query polynomial is compared with zero and one of three possible answers ( < ,=, > ) is returned, each answer leading to a distinct subtree. It is straightforward to simulate a ternary tree with a binary tree at a cost of doubling the size and depth of the tree. However, no simulation in the other direction was previously known. Indeed, Grigoriev et al. [4] have recently shown that if the degree of the query polynomials is bounded by a constant, then there exist binary decision trees for which such a simulation necessarily entails an exponential increase in size. We show that a binary algebraic decision tree T can be converted to a ternary algebraic decision tree T' at the expense of a quadratic increase in size and a linear increase in depth. Received February 15, 1996.     

An improved algorithm for the maximum agreement subtree problem

In this paper, we solve the maximum agreement subtree problem for a set T of k rooted leaf-labeled evolutionary trees on n leaves where T contains a binary tree. We show that the O(kn³)-time dynamic-programming algorithm proposed by Bryant [Building trees, hunting for trees, and comparing trees: theory and methods in phylogenetic analysis, Ph.D. thesis, Dept. Math., University of Canterbury, 1997, pp. 174-182] can be implemented in O(kn²+n²logk−2nloglogn) and O(kn3−1/(k−1)) time by using multidimensional range search related data structures proposed by Gabow et al. [Scaling and related techniques for geometry problems, in: Proc. 16th Annual ACM Symp. on Theory of Computing, 1984, pp. 135-143] and Bentley [Multidimensional binary search trees in database applications, IEEE Trans. Softw. Eng. SE-5 (4) (1979) 333-340], respectively. When k<2+(logn−logloglogn)/(loglogn), the first implementation will be significantly faster than Bryant's algorithm. For k=3, it yields the best known algorithm which runs in O(n²lognloglogn)-time.     

Algorithms for solving the symmetry number problem on trees

The symmetry number of a tree is defined as the number of nodes of the maximum subtree of the tree that exhibits axial symmetry. Chin and Yen have presented an algorithm for solving the problem of finding the symmetry number of unrooted unordered trees in time O(n⁴). In this paper we present an improved algorithm for solving the symmetry number problem on trees that runs in time O(n³). We also show that our algorithm needs O(n²logn) time for trees with bounded degrees.     

A Linear-Time Algorithm for the Feasibility of Pebble Motion on Trees

We consider the following pebble motion problem. We are given a tree T with n vertices and two arrangements and of k<n distinct pebbles numbered 1, . . ., k on distinct vertices of the tree. Pebbles can move along edges of T provided that at any given time at most one pebble is traveling along an edge and each vertex of T contains at most one pebble. We are asked the following question: Is arrangement reachable from ? We present an algorithm that, on input two arrangements of k pebbles on a tree with n vertices, decides in time O(n) whether the two arrangements are reachable from one another. We also give an algorithm that, on input two reachable configurations, returns a sequence of moves that transforms one configuration into the other. The pebble motion problem on trees has various applications including memory management in distributed systems, robot motion planning, and deflection routing. Received August 10, 1996; revised October 1, 1997, and February 17, 1998.     

Finding Largest Subtrees and Smallest Supertrees

As trees are used in a wide variety of application areas, the comparison of trees arises in many guises. Here we consider two generalizations of classical tree pattern matching, which consists of determining if one tree is isomorphic to a subgraph of another. For the embedding problems of subgraph isomorphism and topological embedding, we present algorithms for determining a largest tree embeddable in two trees T and T' (or a largest subtree) and a smallest tree in which each of T and T' can be embedded (or a smallest supertree). Both subtrees and supertrees can be used in a variety of different applications. For example, when each of the two trees contains partial information about a data set, such as the evolution of a set of species, the subtree or supertree corresponds to a structuring of the data in a manner consistent with both original trees. The size of a subtree or supertree of two trees can also be used to measure the similarity between two arrangements of data, whether images, documents, or RNA secondary structures. In this paper we present a general paradigm for sequential and parallel subtree and supertree algorithms for subgraph isomorphism and topological embedding. Our sequential algorithms run in time O(n ^2.5 log n) and our parallel algorithms in time O(log ³ n) on a randomized crew pram using a polynomial number of processors. In addition, we produce better algorithms for these problems when the underlying trees are ordered, that is, when the children of each node have a left-to-right ordering associated with them. In particular, we obtain O(n ² ) -time sequential algorithms and O(log ³ n) -time deterministic parallel algorithms on crew prams for both embeddings. Received July 17, 1995; revised May 25, 1996, and December 10, 1996.     

Rectilinear steiner tree heuristics and minimum spanning tree algorithms using geographic nearest neighbors

We study the application of the geographic nearest neighbor approach to two problems. The first problem is the construction of an approximately minimum length rectilinear Steiner tree for a set ofn points in the plane. For this problem, we introduce a variation of a subgraph of sizeO(n) used by YaO [31] for constructing minimum spanning trees. Using this subgraph, we improve the running times of the heuristics discussed by Bern [6] fromO(n ² log n) toO(n log² n). The second problem is the construction of a rectilinear minimum spanning tree for a set ofn noncrossing line segments in the plane. We present an optimalO(n logn) algorithm for this problem. The rectilinear minimum spanning tree for a set of points can thus be computed optimally without using the Voronoi diagram. This algorithm can also be extended to obtain a rectilinear minimum spanning tree for a set of nonintersecting simple polygons.The results in this paper are a part of Y. C. Yee's Ph.D. thesis done at SUNY at Albany. He was supported in part by NSF Grants IRI-8703430 and CCR-8805782. S. S. Ravi was supported in part by NSF Grants DCI-86-03318 and CCR-89-05296.     

An improved algorithm for finding a length-constrained maximum-density subtree in a tree

Given a tree T with weight and length on each edge, as well as a lower bound L and an upper bound U, the so-called length-constrained maximum-density subtree problem is to find a maximum-density subtree in T such that the length of this subtree is between L and U. In this study, we present an algorithm that runs in O(nUlogn) time for the case when the edge lengths are positive integers, where n is the number of nodes in T, which is an improvement over the previous algorithms when U=Ω(logn). In addition, we show that the time complexity of our algorithm can be reduced to , when the edge lengths being considered are uniform.     

Minimum Cost Partitions of Trees with Supply and Demand

Let T be a given tree. Each vertex of T is either a supply vertex or a demand vertex, and is assigned a positive integer, called the supply or the demand. Every demand vertex v of T must be supplied an amount of ??power,?? equal to the demand of v, from exactly one supply vertex through edges in T. Each edge e of T has a direction, and is assigned a positive integer which represents the cost required to delete e from T or reverse the direction of e. Then one wishes to obtain subtrees of T by deleting edges or reversing the directions of edges so that (a)?each subtree contains exactly one supply vertex whose supply is no less than the sum of all demands in the subtree and (b)?every edge is directed away from the supply vertex in each subtree. One wishes to minimize the total cost to obtain such subtrees from T. In the paper, we first show that this minimization problem is NP-hard, and then give a pseudo-polynomial-time algorithm to solve the problem. We finally give a fully polynomial-time approximation scheme (FPTAS) for the problem.     

ISA [k] trees: A class of binary search trees with minimal or near minimal internal path length

In recent years several authors have investigated binary search trees with minimal internal path length. In this paper we propose relaxing the requirement of inserting all nodes on one level before going to the next level. This leads to a new class of binary search trees called ISA [k] trees. We investigated the average locate cost per node, average shift cost per node, total insertion cost, and average successful search cost for ISA[k] trees. We also present an insertion algorithm with associated predecessor and successor functions for ISA[k] trees. For large binary search trees (over 160 nodes) our results suggest the use of ISA[2] or ISA[3] trees for best performance.     

Some remarks on recognizable treeseries

Let K be a commutative ring, Σ a finite ranked alphabet and T _Σ the set of trees over Σ. We show that for any recognizable treeseries S:T → K having finite range and any subset A of K, the forest of all trees t ? T _Σ such that the corresponding coefficient (s, t) belongs to Ais recognizable.

In the case _Σ collapses to a monadic alphabet, we refind an analogous result concerning rational wordseries due to Schutzenberger [11] and Sontag [12]. Some applications are also given.     

Mining rooted ordered trees under subtree homeomorphism

Mining frequent tree patterns has many applications in different areas such as XML data, bioinformatics and World Wide Web. The crucial step in frequent pattern mining is frequency counting, which involves a matching operator to find occurrences (instances) of a tree pattern in a given collection of trees. A widely used matching operator for tree-structured data is subtree homeomorphism, where an edge in the tree pattern is mapped onto an ancestor-descendant relationship in the given tree. Tree patterns that are frequent under subtree homeomorphism are usually called embedded patterns. In this paper, we present an efficient algorithm for subtree homeomorphism with application to frequent pattern mining. We propose a compact data-structure, called occ, which stores only information about the rightmost paths of occurrences and hence can encode and represent several occurrences of a tree pattern. We then define efficient join operations on the occ data-structure, which help us count occurrences of tree patterns according to occurrences of their proper subtrees. Based on the proposed subtree homeomorphism method, we develop an effective pattern mining algorithm, called TPMiner. We evaluate the efficiency of TPMiner on several real-world and synthetic datasets. Our extensive experiments confirm that TPMiner always outperforms well-known existing algorithms, and in several cases the improvement with respect to existing algorithms is significant.     

Canonical forms for labelled trees and their applications in frequent subtree mining

Tree structures are used extensively in domains such as computational biology, pattern recognition, XML databases, computer networks, and so on. In this paper, we first present two canonical forms for labelled rooted unordered trees–the breadth-first canonical form (BFCF) and the depth-first canonical form (DFCF). Then the canonical forms are applied to the frequent subtree mining problem. Based on the BFCF, we develop a vertical mining algorithm, RootedTreeMiner, to discover all frequently occurring subtrees in a database of labelled rooted unordered trees. The RootedTreeMiner algorithm uses an enumeration tree to enumerate all (frequent) labelled rooted unordered subtrees. Next, we extend the definition of the DFCF to labelled free trees and present an Apriori-like algorithm, FreeTreeMiner, to discover all frequently occurring subtrees in a database of labelled free trees. Finally, we study the performance and the scalability of our algorithms through extensive experiments based on both synthetic data and datasets from real applications.     

Fractional Path Coloring in Bounded Degree Trees with Applications

This paper studies the natural linear programming relaxation of the path coloring problem. We prove constructively that finding an optimal fractional path coloring is Fixed Parameter Tractable (FPT), with the degree of the tree as parameter: the fractional coloring of paths in a bounded degree trees can be done in a time which is linear in the size of the tree, quadratic in the load of the set of paths, while exponential in the degree of the tree. We give an algorithm based on the generation of an efficient polynomial size linear program. Our algorithm is able to explore in polynomial time the exponential number of different fractional colorings, thanks to the notion of trace of a coloring that we introduce. We further give an upper bound on the cost of such a coloring in binary trees and extend this algorithm to bounded degree graphs with bounded treewidth. Finally, we also show some relationships between the integral and fractional problems, and derive a 1+5/3e≈1.61—approximation algorithm for the path coloring problem in bounded degree trees, improving on existing results. This classic combinatorial problem finds applications in the minimization of the number of wavelengths in wavelength division multiplexing (wdm) optical networks.     

The Bit Complexity of Distributed Sorting

We study the bit complexity of the sorting problem for asynchronous distributed systems. We show that for every network with a tree topology T, every sorting algorithm must send at least bits in the worst case, where is the set of possible initial values, and Δ _T is the sum of distances from all the vertices to a median of the tree. In addition, we present an algorithm that sends at most bits for such trees. These bounds are tight if either L=Ω(N ^1+ε ) or Δ _T =Ω(N ² ). We also present results regarding average distributions. These results suggest that sorting is an inherently nondistributive problem, since it requires an amount of information transfer that is equal to the concentration of all the data in a single processor, which then distributes the final results to the whole network. The importance of bit complexity—as opposed to message complexity—stems also from the fact that, in the lower bound discussion, no assumptions are made as to the nature of the algorithm. Received May 2, 1994; revised December 22, 1995.     

Trade-offs Between the Size of Advice and Broadcasting Time in Trees

We study the problem of the amount of information required to perform fast broadcasting in tree networks. The source located at the root of a tree has to disseminate a message to all nodes. In each round each informed node can transmit to one child. Nodes do not know the topology of the tree but an oracle knowing it can give a string of bits of advice to the source which can then pass it down the tree with the source message. The quality of a broadcasting algorithm with advice is measured by its competitive ratio: the worst case ratio, taken over n-node trees, between the time of this algorithm and the optimal broadcasting time in the given tree. Our goal is to find a trade-off between the size of advice and the best competitive ratio of a broadcasting algorithm for n-node trees. We establish such a trade-off with an approximation factor of O(n ^ε ), for an arbitrarily small positive constant ε. This is the first communication problem for which a trade-off between the size of advice and the efficiency of the solution is shown for arbitrary size of advice.