504 research outputs found
Reasoning & Querying – State of the Art
Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF
Impossibility results on stability of phylogenetic consensus methods
We answer two questions raised by Bryant, Francis and Steel in their work on
consensus methods in phylogenetics. Consensus methods apply to every practical
instance where it is desired to aggregate a set of given phylogenetic trees
(say, gene evolution trees) into a resulting, "consensus" tree (say, a species
tree). Various stability criteria have been explored in this context, seeking
to model desirable consistency properties of consensus methods as the
experimental data is updated (e.g., more taxa, or more trees, are mapped).
However, such stability conditions can be incompatible with some basic
regularity properties that are widely accepted to be essential in any
meaningful consensus method. Here, we prove that such an incompatibility does
arise in the case of extension stability on binary trees and in the case of
associative stability. Our methods combine general theoretical considerations
with the use of computer programs tailored to the given stability requirements
Near-optimal labeling schemes for nearest common ancestors
We consider NCA labeling schemes: given a rooted tree , label the nodes of
with binary strings such that, given the labels of any two nodes, one can
determine, by looking only at the labels, the label of their nearest common
ancestor.
For trees with nodes we present upper and lower bounds establishing that
labels of size , are both sufficient and
necessary. (All logarithms in this paper are in base 2.)
Alstrup, Bille, and Rauhe (SIDMA'05) showed that ancestor and NCA labeling
schemes have labels of size . Our lower bound
increases this to for NCA labeling schemes. Since
Fraigniaud and Korman (STOC'10) established that labels in ancestor labeling
schemes have size , our new lower bound separates
ancestor and NCA labeling schemes. Our upper bound improves the
upper bound by Alstrup, Gavoille, Kaplan and Rauhe (TOCS'04), and our
theoretical result even outperforms some recent experimental studies by Fischer
(ESA'09) where variants of the same NCA labeling scheme are shown to all have
labels of size approximately
Optimizing Phylogenetic Supertrees Using Answer Set Programming
The supertree construction problem is about combining several phylogenetic
trees with possibly conflicting information into a single tree that has all the
leaves of the source trees as its leaves and the relationships between the
leaves are as consistent with the source trees as possible. This leads to an
optimization problem that is computationally challenging and typically
heuristic methods, such as matrix representation with parsimony (MRP), are
used. In this paper we consider the use of answer set programming to solve the
supertree construction problem in terms of two alternative encodings. The first
is based on an existing encoding of trees using substructures known as
quartets, while the other novel encoding captures the relationships present in
trees through direct projections. We use these encodings to compute a
genus-level supertree for the family of cats (Felidae). Furthermore, we compare
our results to recent supertrees obtained by the MRP method.Comment: To appear in Theory and Practice of Logic Programming (TPLP),
Proceedings of ICLP 201
Querying XML Documents Made Easy: Nearest Concept Queries
Due to the ubiquity and popularity of XML, users often are in the following situation: they want to query XML documents which contain potentially interesting information but they are unaware of the mark-up structure that is used. For example, it is easy to guess the contents of an XML bibliography file whereas the mark-up depends on the methodological, cultural and personal background of the author(s). Nonetheless, it is this hierarchical structure that forms the basis of XML query languages.
In this paper we exploit the tree structure of XML documents to equip users with a powerful tool, the meet operator, that lets them query databases with whose content they are familiar, but without requiring knowledge of tags and hierarchies. Our approach is based on computing the lowest common ancestor of nodes in the XML syntax tree: eg, given two strings, we are looking for nodes whose offspring contains these two strings. The novelty of this approach is that the result type is unknown at query formulation time and dependent on the database instance. If the two strings are an author's name and a year, mainly publications of the author in this year are returned. If the two strings are numbers the result mostly consists of publications that have the numbers as year or page numbers. Because the result type of a query is not specified by the user we refer to the lowest common ancestor as nearest concept
We also present a running example taken from the bibliography domain, and demonstrate that the operator can be implemented efficiently
Tree Contractions and Evolutionary Trees
An evolutionary tree is a rooted tree where each internal vertex has at least
two children and where the leaves are labeled with distinct symbols
representing species. Evolutionary trees are useful for modeling the
evolutionary history of species. An agreement subtree of two evolutionary trees
is an evolutionary tree which is also a topological subtree of the two given
trees. We give an algorithm to determine the largest possible number of leaves
in any agreement subtree of two trees T_1 and T_2 with n leaves each. If the
maximum degree d of these trees is bounded by a constant, the time complexity
is O(n log^2(n)) and is within a log(n) factor of optimal. For general d, this
algorithm runs in O(n d^2 log(d) log^2(n)) time or alternatively in O(n d
sqrt(d) log^3(n)) time
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