36,539 research outputs found
Integrated Node Encoder for Labelled Textual Networks
Voluminous works have been implemented to exploit content-enhanced network
embedding models, with little focus on the labelled information of nodes.
Although TriDNR leverages node labels by treating them as node attributes, it
fails to enrich unlabelled node vectors with the labelled information, which
leads to the weaker classification result on the test set in comparison to
existing unsupervised textual network embedding models. In this study, we
design an integrated node encoder (INE) for textual networks which is jointly
trained on the structure-based and label-based objectives. As a result, the
node encoder preserves the integrated knowledge of not only the network text
and structure, but also the labelled information. Furthermore, INE allows the
creation of label-enhanced vectors for unlabelled nodes by entering their node
contents. Our node embedding achieves state-of-the-art performances in the
classification task on two public citation networks, namely Cora and DBLP,
pushing benchmarks up by 10.0\% and 12.1\%, respectively, with the 70\%
training ratio. Additionally, a feasible solution that generalizes our model
from textual networks to a broader range of networks is proposed.Comment: 7 page
A Novel Distributed Representation of News (DRNews) for Stock Market Predictions
In this study, a novel Distributed Representation of News (DRNews) model is
developed and applied in deep learning-based stock market predictions. With the
merit of integrating contextual information and cross-documental knowledge, the
DRNews model creates news vectors that describe both the semantic information
and potential linkages among news events through an attributed news network.
Two stock market prediction tasks, namely the short-term stock movement
prediction and stock crises early warning, are implemented in the framework of
the attention-based Long Short Term-Memory (LSTM) network. It is suggested that
DRNews substantially enhances the results of both tasks comparing with five
baselines of news embedding models. Further, the attention mechanism suggests
that short-term stock trend and stock market crises both receive influences
from daily news with the former demonstrates more critical responses on the
information related to the stock market {\em per se}, whilst the latter draws
more concerns on the banking sector and economic policies.Comment: 25 page
The Fenchel-type inequality in the 3-dimensional Lorentz space and a Crofton formula
We generalize the Fenchel theorem to strong spacelike (which means that the
tangent vector and the curvature vector span a spacelike 2-plane at each point)
closed curves with index 1 in the 3-dimensional Lorentz space, showing that the
total curvatures must be less than or equal to . A similar generalization
of the Fary-Milnor theorem is also obtained. We establish the Crofton formula
on the de Sitter 2-sphere which implies the above results.Comment: 9 pages, 4 figures. Comments are welcom
Ultrasensitive detections in atomic and molecular physics: demonstration in molecular overtone spectroscopy
We consider several highly sensitive techniques commonly used in detection of atomic and molecular absorptions. Their basic operating principles and corresponding performances are summarized and compared. We then present our latest results on the ultrasensitive detection of molecular overtone transitions to illustrate the principle and application of the cavity-enhanced frequency-modulation (FM) spectroscopy. An external cavity is used to enhance the molecular response to the light field, and an FM technique is applied for shot-noise-limited signal recovery. A perfect match between the FM sideband frequency and the cavity free spectral range makes the detection process insensitive to the laser-frequency noise relative to the cavity, and, at the same time, overcomes the cavity bandwidth limit. Working with a 1.064-µm Nd:YAG laser, we obtained sub-Doppler overtone resonances of C2HD, C2H2, and CO2 molecules. A detection sensitivity of 5 x 10^-13 of integrated absorption (1 x 10^-14/cm) over 1-s averaging time has been achieved
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