8,586 research outputs found
Exposing Multi-Relational Networks to Single-Relational Network Analysis Algorithms
Many, if not most network analysis algorithms have been designed specifically
for single-relational networks; that is, networks in which all edges are of the
same type. For example, edges may either represent "friendship," "kinship," or
"collaboration," but not all of them together. In contrast, a multi-relational
network is a network with a heterogeneous set of edge labels which can
represent relationships of various types in a single data structure. While
multi-relational networks are more expressive in terms of the variety of
relationships they can capture, there is a need for a general framework for
transferring the many single-relational network analysis algorithms to the
multi-relational domain. It is not sufficient to execute a single-relational
network analysis algorithm on a multi-relational network by simply ignoring
edge labels. This article presents an algebra for mapping multi-relational
networks to single-relational networks, thereby exposing them to
single-relational network analysis algorithms.Comment: ISSN:1751-157
Robust Grammatical Analysis for Spoken Dialogue Systems
We argue that grammatical analysis is a viable alternative to concept
spotting for processing spoken input in a practical spoken dialogue system. We
discuss the structure of the grammar, and a model for robust parsing which
combines linguistic sources of information and statistical sources of
information. We discuss test results suggesting that grammatical processing
allows fast and accurate processing of spoken input.Comment: Accepted for JNL
Controlled non uniform random generation of decomposable structures
Consider a class of decomposable combinatorial structures, using different
types of atoms \Atoms = \{\At_1,\ldots ,\At_{|{\Atoms}|}\}. We address the
random generation of such structures with respect to a size and a targeted
distribution in of its \emph{distinguished} atoms. We consider two
variations on this problem. In the first alternative, the targeted distribution
is given by real numbers \TargFreq_1, \ldots, \TargFreq_k such that 0 <
\TargFreq_i < 1 for all and \TargFreq_1+\cdots+\TargFreq_k \leq 1. We
aim to generate random structures among the whole set of structures of a given
size , in such a way that the {\em expected} frequency of any distinguished
atom \At_i equals \TargFreq_i. We address this problem by weighting the
atoms with a -tuple \Weights of real-valued weights, inducing a weighted
distribution over the set of structures of size . We first adapt the
classical recursive random generation scheme into an algorithm taking
\bigO{n^{1+o(1)}+mn\log{n}} arithmetic operations to draw structures from
the \Weights-weighted distribution. Secondly, we address the analytical
computation of weights such that the targeted frequencies are achieved
asymptotically, i. e. for large values of . We derive systems of functional
equations whose resolution gives an explicit relationship between \Weights
and \TargFreq_1, \ldots, \TargFreq_k. Lastly, we give an algorithm in
\bigO{k n^4} for the inverse problem, {\it i.e.} computing the frequencies
associated with a given -tuple \Weights of weights, and an optimized
version in \bigO{k n^2} in the case of context-free languages. This allows
for a heuristic resolution of the weights/frequencies relationship suitable for
complex specifications. In the second alternative, the targeted distribution is
given by a natural numbers such that
where is the number of undistinguished atoms.
The structures must be generated uniformly among the set of structures of size
that contain {\em exactly} atoms \At_i (). We give
a \bigO{r^2\prod_{i=1}^k n_i^2 +m n k \log n} algorithm for generating
structures, which simplifies into a \bigO{r\prod_{i=1}^k n_i +m n} for
regular specifications
Research on Architectures for Integrated Speech/Language Systems in Verbmobil
The German joint research project Verbmobil (VM) aims at the development of a
speech to speech translation system. This paper reports on research done in our
group which belongs to Verbmobil's subproject on system architectures (TP15).
Our specific research areas are the construction of parsers for spontaneous
speech, investigations in the parallelization of parsing and to contribute to
the development of a flexible communication architecture with distributed
control.Comment: 6 pages, 2 Postscript figure
On Dependency Analysis via Contractions and Weighted FSTs
Arc contractions in syntactic dependency graphs can be used to decide which graphs are trees. The paper observes that these contractions can be expressed with weighted finite-state transducers (weighted FST) that operate on string-encoded trees. The observation gives rise to a finite-state parsing algorithm that computes the parse forest and extracts the best parses from it. The algorithm is customizable to functional and bilexical dependency parsing, and it can be extended to non-projective parsing via a multi-planar encoding with prior results on high recall. Our experiments support an analysis of projective parsing according to which the worst-case time complexity of the algorithm is quadratic to the sentence length, and linear to the overlapping arcs and the number of functional categories of the arcs. The results suggest several interesting directions towards efficient and highprecision dependency parsing that takes advantage of the flexibility and the demonstrated ambiguity-packing capacity of such a parser.Peer reviewe
Chemoinformatics Research at the University of Sheffield: A History and Citation Analysis
This paper reviews the work of the Chemoinformatics Research Group in the Department of Information Studies at the University of Sheffield, focusing particularly on the work carried out in the period 1985-2002. Four major research areas are discussed, these involving the development of methods for: substructure searching in databases of three-dimensional structures, including both rigid and flexible molecules; the representation and searching of the Markush structures that occur in chemical patents; similarity searching in databases of both two-dimensional and three-dimensional structures; and compound selection and the design of combinatorial libraries. An analysis of citations to 321 publications from the Group shows that it attracted a total of 3725 residual citations during the period 1980-2002. These citations appeared in 411 different journals, and involved 910 different citing organizations from 54 different countries, thus demonstrating the widespread impact of the Group's work
Grasp: Randomised Semiring Parsing
We present a suite of algorithms for inference tasks over (finite and infinite) context-free sets. For generality and clarity, we have chosen the framework of semiring parsing with support to the most common semirings (e.g. Forest, Viterbi, k-best and Inside). We see parsing from the more general viewpoint of weighted deduction allowing for arbitrary weighted finite-state input and provide implementations of both bottom-up (CKY-inspired) and top-down (Earley-inspired) algorithms. We focus on approximate inference by Monte Carlo methods and provide implementations of ancestral sampling and slice sampling. In principle, sampling methods can deal with models whose independence assumptions are weaker than what is feasible by standard dynamic programming. We envision applications such as monolingual constituency parsing, synchronous parsing, context-free models of reordering for machine translation, and machine translation decoding
Grounding semantics in robots for Visual Question Answering
In this thesis I describe an operational implementation of an object detection and description system that incorporates in an end-to-end Visual Question Answering system and evaluated it on two visual question answering datasets for compositional language and elementary visual reasoning
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