2,624 research outputs found
Unsupervised Entailment Detection between Dependency Graph Fragments
Entailment detection systems are generally
designed to work either on single words, relations
or full sentences. We propose a new
task – detecting entailment between dependency
graph fragments of any type – which
relaxes these restrictions and leads to much
wider entailment discovery. An unsupervised
framework is described that uses intrinsic similarity,
multi-level extrinsic similarity and the
detection of negation and hedged language to
assign a confidence score to entailment relations
between two fragments. The final system
achieves 84.1% average precision on a data set
of entailment examples from the biomedical
domain
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Parser lexicalisation through self-learning
We describe a new self-learning framework for parser lexicalisation that requires only a plain-text corpus of in-domain text. The method first creates augmented versions of dependency graphs by applying a series of modifications designed to directly capture higherorder lexical path dependencies. Scores are assigned to each edge in the graph using statistics from an automatically parsed background corpus. As bilexical dependencies are sparse, a novel directed distributional word similarity measure is used to smooth edge score estimates. Edge scores are then combined into graph scores and used for reranking the topn analyses found by the unlexicalised parser. The approach achieves significant improvements on WSJ and biomedical text over the unlexicalised baseline parser, which is originally trained on a subset of the Brown corpus
Constrained multi-task learning for automated essay scoring
Supervised machine learning models for
automated essay scoring (AES) usually require
substantial task-specific training data
in order to make accurate predictions for
a particular writing task. This limitation
hinders their utility, and consequently
their deployment in real-world settings. In
this paper, we overcome this shortcoming
using a constrained multi-task pairwisepreference
learning approach that enables
the data from multiple tasks to be combined
effectively.
Furthermore, contrary to some recent research,
we show that high performance
AES systems can be built with little or no
task-specific training data. We perform a
detailed study of our approach on a publicly
available dataset in scenarios where
we have varying amounts of task-specific
training data and in scenarios where the
number of tasks increases.This is the author accepted manuscript. The final version is available from Association for Computational Linguistics at http://acl2016.org/index.php?article_id=71
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Automatic extraction of learner errors in ESL sentences using linguistically enhanced alignments
We propose a new method of automatically extracting learner errors from parallel English as a Second Language (ESL) sentences in an effort to regularise annotation formats and reduce inconsistencies. Specifically, given an original and corrected sentence, our method first uses a linguistically enhanced alignment algorithm to determine the most likely mappings between tokens, and secondly employs a rule-based function to decide which alignments should be merged. Our method beats all previous approaches on the tested datasets, achieving state-of-the-art results for automatic error extraction.This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by the Association for Computational Linguistics
Mortification and Apodiorizo: Re-framing Apologia
Image restoration strategies and apologia have been used for years to explain how speakers engage in verbal self-defense. Kategoria has expanded our understanding of apologia when rhetors counter with an accusation to explain or justify their behavior. In recent years, however, a new tactic has emerged in apologia in which speakers admit to the transgression but then accuse the media of invading their privacy by stalking their families. Following the accusation, these speakers draw a boundary with the media and the audience regarding what the media can and cannot do. This strategy is unique because the rhetor does not attempt to create a scapegoat. The rhetor takes full responsibility for the transgression, sometimes even taunting the media to “come after me,” but then demands the media leave their family alone. This strategy of bringing a charge and drawing a boundary is absent in current image restoration literature. This essay will identify this new rhetorical posture as apodiorizo
London Creative and Digital Fusion
date-added: 2015-03-24 04:16:59 +0000 date-modified: 2015-03-24 04:16:59 +0000date-added: 2015-03-24 04:16:59 +0000 date-modified: 2015-03-24 04:16:59 +0000The London Creative and Digital Fusion programme of interactive, tailored and in-depth support was designed to support the UK capital’s creative and digital companies to collaborate, innovate and grow. London is a globally recognised hub for technology, design and creative genius. While many cities around the world can claim to be hubs for technology entrepreneurship, London’s distinctive potential lies in the successful fusion of world-leading technology with world-leading design and creativity. As innovation thrives at the edge, where better to innovate than across the boundaries of these two clusters and cultures? This booklet tells the story of Fusion’s innovation journey, its partners and its unique business support. Most importantly of all it tells stories of companies that, having worked with London Fusion, have innovated and grown. We hope that it will inspire others to follow and build on our beginnings.European Regional Development Fund 2007-13
Phase transition and hysteresis in scale-free network traffic
We model information traffic on scale-free networks by introducing the node
queue length L proportional to the node degree and its delivering ability C
proportional to L. The simulation gives the overall capacity of the traffic
system, which is quantified by a phase transition from free flow to congestion.
It is found that the maximal capacity of the system results from the case of
the local routing coefficient \phi slightly larger than zero, and we provide an
analysis for the optimal value of \phi. In addition, we report for the first
time the fundamental diagram of flow against density, in which hysteresis is
found, and thus we can classify the traffic flow with four states: free flow,
saturated flow, bistable, and jammed.Comment: 5 pages, 4 figure
Video sensor with range measurement capability
A video sensor device is provided which incorporates a rangefinder function. The device includes a single video camera and a fixed laser spaced a predetermined distance from the camera for, when activated, producing a laser beam. A diffractive optic element divides the beam so that multiple light spots are produced on a target object. A processor calculates the range to the object based on the known spacing and angles determined from the light spots on the video images produced by the camera
Non-Amontons behavior of friction in single contacts
We report on the frictional properties of a single contact between a glassy
polymer lens and a flat silica substrate covered either by a disordered or by a
self-assembled alkylsilane monolayer. We find that, in contrast to common
belief, the Amontons proportionality between frictional and normal stresses
does not hold. Besides, we observe that the velocity dependence of the sliding
stress is strongly sensitive to the structure of the silane layer. Analysis of
the frictional rheology observed on both disordered and self-assembled
monolayers suggests that dissipation is controlled by the plasticity of a
glass-like interfacial layer in the former case, and by pinning of polymer
chains on the substrate in the latter one.Comment: submitted to Eur. Phys. J.
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