12,958 research outputs found
Structural Regularities in Text-based Entity Vector Spaces
Entity retrieval is the task of finding entities such as people or products
in response to a query, based solely on the textual documents they are
associated with. Recent semantic entity retrieval algorithms represent queries
and experts in finite-dimensional vector spaces, where both are constructed
from text sequences.
We investigate entity vector spaces and the degree to which they capture
structural regularities. Such vector spaces are constructed in an unsupervised
manner without explicit information about structural aspects. For concreteness,
we address these questions for a specific type of entity: experts in the
context of expert finding. We discover how clusterings of experts correspond to
committees in organizations, the ability of expert representations to encode
the co-author graph, and the degree to which they encode academic rank. We
compare latent, continuous representations created using methods based on
distributional semantics (LSI), topic models (LDA) and neural networks
(word2vec, doc2vec, SERT). Vector spaces created using neural methods, such as
doc2vec and SERT, systematically perform better at clustering than LSI, LDA and
word2vec. When it comes to encoding entity relations, SERT performs best.Comment: ICTIR2017. Proceedings of the 3rd ACM International Conference on the
Theory of Information Retrieval. 201
Good Applications for Crummy Entity Linkers? The Case of Corpus Selection in Digital Humanities
Over the last decade we have made great progress in entity linking (EL)
systems, but performance may vary depending on the context and, arguably, there
are even principled limitations preventing a "perfect" EL system. This also
suggests that there may be applications for which current "imperfect" EL is
already very useful, and makes finding the "right" application as important as
building the "right" EL system. We investigate the Digital Humanities use case,
where scholars spend a considerable amount of time selecting relevant source
texts. We developed WideNet; a semantically-enhanced search tool which
leverages the strengths of (imperfect) EL without getting in the way of its
expert users. We evaluate this tool in two historical case-studies aiming to
collect a set of references to historical periods in parliamentary debates from
the last two decades; the first targeted the Dutch Golden Age, and the second
World War II. The case-studies conclude with a critical reflection on the
utility of WideNet for this kind of research, after which we outline how such a
real-world application can help to improve EL technology in general.Comment: Accepted for presentation at SEMANTiCS '1
Picturing words: The semantics of speech balloons
Semantics traditionally focuses on linguistic meaning. In recent years, the Super Linguistics movement has tried to broaden the scope of inquiry in various directions, including an extension of semantics to talk about the meaning of pictures. There are close similarities between the interpretation of language and of pictures. Most fundamentally, pictures, like utterances, can be either true or false of a given state of affairs, and hence both express propositions (Zimmermann, 2016; Greenberg, 2013; Abusch, 2015). Moreover, sequences of pictures, like sequences of utterances, can be used to tell stories. Wordless picture books, comics, and film are cases in point. In this paper I pick up the project of providing a dynamic semantic account of pictorial story-telling, started by Abusch (2012) and continued by Abusch & Rooth (2017); Maier & Bimpikou (2019); Fernando (2020). More specifically, I propose here a semantics of speech and thought bubbles by adding event reference to PicDRT. To get there I first review the projection-based semantics for pictures (section 1), noting the fundamental distinction between symbolic and iconic meaning that makes speech bubbles especially interesting (section 2). I then review the dynamic PicDRT framework for pictorial narratives (section 3), add events (section 4), and propose an account of speech bubbles as quotational event modification (section 5). I end with a brief look at other conventional, symbolic enrichments in comics (section 6)
Complex copula systems as suppletive alomorphy
Languages are known to vary in the number of verbs they exhibit corresponding to English "be", in the distribution of such copular verbs, and in the presence or absence of a
distinct verb for possession sentences corresponding to English
"have". This paper offers novel
arguments for the position that such differences should be modeled in terms of suppletive
allomorphy of the same syntactic element (here dubbed v BE), employing a Late Insertion-
based framework. It is shown that such a suppletive allomorphy approach to complex copula
systems makes three predictions that distinguish it from non-suppletion-based alternatives
(concerning decomposition, possible and impossible syncretisms, and Impoverishment), and that these predictions seem to be correct (although a full test of the possible and impossible syncretisms prediction is not possible in the current state of knowledge)
Dynamic Adaptive Point Cloud Streaming
High-quality point clouds have recently gained interest as an emerging form
of representing immersive 3D graphics. Unfortunately, these 3D media are bulky
and severely bandwidth intensive, which makes it difficult for streaming to
resource-limited and mobile devices. This has called researchers to propose
efficient and adaptive approaches for streaming of high-quality point clouds.
In this paper, we run a pilot study towards dynamic adaptive point cloud
streaming, and extend the concept of dynamic adaptive streaming over HTTP
(DASH) towards DASH-PC, a dynamic adaptive bandwidth-efficient and view-aware
point cloud streaming system. DASH-PC can tackle the huge bandwidth demands of
dense point cloud streaming while at the same time can semantically link to
human visual acuity to maintain high visual quality when needed. In order to
describe the various quality representations, we propose multiple thinning
approaches to spatially sub-sample point clouds in the 3D space, and design a
DASH Media Presentation Description manifest specific for point cloud
streaming. Our initial evaluations show that we can achieve significant
bandwidth and performance improvement on dense point cloud streaming with minor
negative quality impacts compared to the baseline scenario when no adaptations
is applied.Comment: 6 pages, 23rd ACM Packet Video (PV'18) Workshop, June 12--15, 2018,
Amsterdam, Netherland
Sequential Composition in the Presence of Intermediate Termination (Extended Abstract)
The standard operational semantics of the sequential composition operator
gives rise to unbounded branching and forgetfulness when transparent process
expressions are put in sequence. Due to transparency, the correspondence
between context-free and pushdown processes fails modulo bisimilarity, and it
is not clear how to specify an always terminating half counter. We propose a
revised operational semantics for the sequential composition operator in the
context of intermediate termination. With the revised operational semantics, we
eliminate transparency, allowing us to establish a close correspondence between
context-free processes and pushdown processes. Moreover, we prove the reactive
Turing powerfulness of TCP with iteration and nesting with the revised
operational semantics for sequential composition.Comment: In Proceedings EXPRESS/SOS 2017, arXiv:1709.00049. arXiv admin note:
substantial text overlap with arXiv:1706.0840
Pixelated Semantic Colorization
While many image colorization algorithms have recently shown the capability
of producing plausible color versions from gray-scale photographs, they still
suffer from limited semantic understanding. To address this shortcoming, we
propose to exploit pixelated object semantics to guide image colorization. The
rationale is that human beings perceive and distinguish colors based on the
semantic categories of objects. Starting from an autoregressive model, we
generate image color distributions, from which diverse colored results are
sampled. We propose two ways to incorporate object semantics into the
colorization model: through a pixelated semantic embedding and a pixelated
semantic generator. Specifically, the proposed convolutional neural network
includes two branches. One branch learns what the object is, while the other
branch learns the object colors. The network jointly optimizes a color
embedding loss, a semantic segmentation loss and a color generation loss, in an
end-to-end fashion. Experiments on PASCAL VOC2012 and COCO-stuff reveal that
our network, when trained with semantic segmentation labels, produces more
realistic and finer results compared to the colorization state-of-the-art
Logic and Topology for Knowledge, Knowability, and Belief - Extended Abstract
In recent work, Stalnaker proposes a logical framework in which belief is
realized as a weakened form of knowledge. Building on Stalnaker's core
insights, and using frameworks developed by Bjorndahl and Baltag et al., we
employ topological tools to refine and, we argue, improve on this analysis. The
structure of topological subset spaces allows for a natural distinction between
what is known and (roughly speaking) what is knowable; we argue that the
foundational axioms of Stalnaker's system rely intuitively on both of these
notions. More precisely, we argue that the plausibility of the principles
Stalnaker proposes relating knowledge and belief relies on a subtle
equivocation between an "evidence-in-hand" conception of knowledge and a weaker
"evidence-out-there" notion of what could come to be known. Our analysis leads
to a trimodal logic of knowledge, knowability, and belief interpreted in
topological subset spaces in which belief is definable in terms of knowledge
and knowability. We provide a sound and complete axiomatization for this logic
as well as its uni-modal belief fragment. We then consider weaker logics that
preserve suitable translations of Stalnaker's postulates, yet do not allow for
any reduction of belief. We propose novel topological semantics for these
irreducible notions of belief, generalizing our previous semantics, and provide
sound and complete axiomatizations for the corresponding logics.Comment: In Proceedings TARK 2017, arXiv:1707.08250. The full version of this
paper, including the longer proofs, is at arXiv:1612.0205
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