pinecone/core-2020-05-10-deduplication huggingface dataset:
Document Clustering Games in Static and Dynamic Scenarios

In this work we propose a game theoretic model for document clustering. Each
document to be clustered is represented as a player and each cluster as a
strategy. The players receive a reward interacting with other players that they
try to maximize choosing their best strategies. The geometry of the data is
modeled with a weighted graph that encodes the pairwise similarity among
documents, so that similar players are constrained to choose similar
strategies, updating their strategy preferences at each iteration of the games.
We used different approaches to find the prototypical elements of the clusters
and with this information we divided the players into two disjoint sets, one
collecting players with a definite strategy and the other one collecting
players that try to learn from others the correct strategy to play. The latter
set of players can be considered as new data points that have to be clustered
according to previous information. This representation is useful in scenarios
in which the data are streamed continuously. The evaluation of the system was
conducted on 13 document datasets using different settings. It shows that the
proposed method performs well compared to different document clustering
algorithms.Comment: This paper will be published in the series Lecture Notes in Computer
  Science (LNCS) published by Springer, containing the ICPRAM 2016 best paper
Approximate inference in related multi-output Gaussian Process Regression

In Gaussian Processes a multi-output kernel is a covariance function over correlated outputs. Using a prior known relation between outputs, joint auto- and cross-covariance functions can be constructed. Realizations from these joint-covariance functions give outputs that are consistent with the prior relation. One issue with gaussian process regression is efficient inference when scaling upto large datasets. In this paper we use approximate inference techniques upon multi-output kernels enforcing relationships between outputs. Results of the proposed methodology for theoretical data and real world applications are presented. The main contribution of this paper is the application and validation of our methodology on a dataset of real aircraft fight tests, while imposing knowledge of aircraft physics into the model
Monogamy of quantum correlations - a review

Monogamy is an intrinsic feature of quantum correlations that gives rise to
several interesting quantum characteristics which are not amenable to classical
explanations. The monogamy property imposes physical restrictions on
unconditional sharability of quantum correlations between the different parts
of a multipartite quantum system, and thus has a direct bearing on the
cooperative properties of states of multiparty systems, including large
many-body systems. On the contrary, a certain party can be maximally classical
correlated with an arbitrary number of parties in a multiparty system. In
recent years, the monogamy property of quantum correlations has been applied to
understand several key aspects of quantum physics, including distribution of
quantum resources, security in quantum communication, critical phenomena, and
quantum biology. In this chapter, we look at some of the salient developments
and applications in quantum physics that have been closely associated with the
monogamy of quantum discord, and "discord-like" quantum correlation measures.Comment: 21 pages, 6 figure
Entanglement distribution and quantum discord

Establishing entanglement between distant parties is one of the most
important problems of quantum technology, since long-distance entanglement is
an essential part of such fundamental tasks as quantum cryptography or quantum
teleportation. In this lecture we review basic properties of entanglement and
quantum discord, and discuss recent results on entanglement distribution and
the role of quantum discord therein. We also review entanglement distribution
with separable states, and discuss important problems which still remain open.
One such open problem is a possible advantage of indirect entanglement
distribution, when compared to direct distribution protocols.Comment: 7 pages, 2 figures, contribution to "Lectures on general quantum
  correlations and their applications", edited by Felipe Fanchini, Diogo
  Soares-Pinto, and Gerardo Adess
Discord, quantum knowledge and private communications

In this brief review, we discuss the role that quantum correlations, as
quantified by quantum discord, play in two interesting settings. The first one
is discerning which unitaries have been applied on a quantum system, by taking
advantage of knowledge regarding its initial configuration. Here discord
captures the "quantum" component of this knowledge, useful only when we have
access to a quantum memory. In particular, discord can be used to detect
whether an untrusted party has certain quantum capabilities. The second setting
is quantum cryptography. Here discord represents an important resource for
trusted-noise quantum key distribution and also provides a general upper bound
for the optimal secret key rates that are achievable by ideal protocols. In
particular, the (two-way assisted) secret key capacity of a lossy bosonic
channel exactly coincides with the maximum discord that can be distributed
between the remote parties at the two ends of the channel.Comment: REVTeX. 5 pages, 1 figur
The sudden change phenomenon of quantum discord

Even if the parameters determining a system's state are varied smoothly, the
behavior of quantum correlations alike to quantum discord, and of its classical
counterparts, can be very peculiar, with the appearance of non-analyticities in
its rate of change. Here we review this sudden change phenomenon (SCP)
discussing some important points related to it: Its uncovering,
interpretations, and experimental verifications, its use in the context of the
emergence of the pointer basis in a quantum measurement process, its appearance
and universality under Markovian and non-Markovian dynamics, its theoretical
and experimental investigation in some other physical scenarios, and the
related phenomenon of double sudden change of trace distance discord. Several
open questions are identified, and we envisage that in answering them we will
gain significant further insight about the relation between the SCP and the
symmetry-geometric aspects of the quantum state space.Comment: Lectures on General Quantum Correlations and their Applications, F.
  F. Fanchini, D. O. Soares Pinto, and G. Adesso (Eds.), Springer (2017), pp
  309-33
Overview on the phenomenon of two-qubit entanglement revivals in
  classical environments

The occurrence of revivals of quantum entanglement between separated open
quantum systems has been shown not only for dissipative non-Markovian quantum
environments but also for classical environments in absence of back-action.
While the phenomenon is well understood in the first case, the possibility to
retrieve entanglement when the composite quantum system is subject to local
classical noise has generated a debate regarding its interpretation. This
dynamical property of open quantum systems assumes an important role in quantum
information theory from both fundamental and practical perspectives. Hybrid
quantum-classical systems are in fact promising candidates to investigate the
interplay among quantum and classical features and to look for possible control
strategies of a quantum system by means of a classical device. Here we present
an overview on this topic, reporting the most recent theoretical and
experimental results about the revivals of entanglement between two qubits
locally interacting with classical environments. We also review and discuss the
interpretations provided so far to explain this phenomenon, suggesting that
they can be cast under a unified viewpoint.Comment: 16 pages, 9 figures. Chapter written for the upcoming book "Lectures
  on general quantum correlations and their applications
Quantum correlations and synchronization measures

The phenomenon of spontaneous synchronization is universal and only recently
advances have been made in the quantum domain. Being synchronization a kind of
temporal correlation among systems, it is interesting to understand its
connection with other measures of quantum correlations. We review here what is
known in the field, putting emphasis on measures and indicators of
synchronization which have been proposed in the literature, and comparing their
validity for different dynamical systems, highlighting when they give similar
insights and when they seem to fail.Comment: book chapter, 18 pages, 7 figures, Fanchini F., Soares Pinto D.,
  Adesso G. (eds) Lectures on General Quantum Correlations and their
  Applications. Quantum Science and Technology. Springer (2017
How does interference fall?

We study how single- and double-slit interference patterns fall in the
presence of gravity. First, we demonstrate that universality of free fall still
holds in this case, i.e., interference patterns fall just like classical
objects. Next, we explore lowest order relativistic effects in the Newtonian
regime by employing a recent quantum formalism which treats mass as an
operator. This leads to interactions between non-degenerate internal degrees of
freedom (like spin in an external magnetic field) and external degrees of
freedom (like position). Based on these effects, we present an unusual
phenomenon, in which a falling double slit interference pattern periodically
decoheres and recoheres. The oscillations in the visibility of this
interference occur due to correlations built up between spin and position.
Finally, we connect the interference visibility revivals with non-Markovian
quantum dynamics.Comment: Contribution to "Lectures on general quantum correlations and their
  applications", edited by Felipe Fanchini, Diogo Soares-Pinto, and Gerardo
  Adess
Quantum Correlations in NMR systems

In conventional NMR experiments, the Zeeman energy gaps of the nuclear spin
ensembles are much lower than their thermal energies, and accordingly exhibit
tiny polarizations. Generally such low-purity quantum states are devoid of
quantum entanglement. However, there exist certain nonclassical correlations
which can be observed even in such systems. In this chapter, we discuss three
such quantum correlations, namely, quantum contextuality, Leggett-Garg temporal
correlations, and quantum discord. In each case, we provide a brief theoretical
background and then describe some results from NMR experiments.Comment: 21 pages, 7 figure
Why should we care about quantum discord?

Entanglement is a central feature of quantum theory. Mathematical properties
and physical applications of pure state entanglement make it a template to
study quantum correlations. However, an extension of entanglement measures to
mixed states in terms of separability does not always correspond to all the
operational aspects. Quantum discord measures allow an alternative way to
extend the idea of quantum correlations to mixed states. In many cases these
extensions are motivated by physical scenarios and quantum information
protocols. In this chapter we discuss several settings involving correlated
quantum systems, ranging from distributed gates to detectors testing quantum
fields. In each setting we show how entanglement fails to capture the relevant
features of the correlated system, and discuss the role of discord as a
possible alternative.Comment: Written for "Lectures on general quantum correlations and their
  applications
Detection of behavioral patterns for increasing attentiveness level

In the current world, performance is one of the most important issues
concerning work and competition. Performance is strongly connected with
learning and when it comes to acquiring new knowledge, attention is one the
most important mechanisms as the level of the learner’s attention affects learning
results. When students are doing learning activities using new technologies,
it is extremely important that the teacher has some feedback from the students’
work in order to detect potential learning problems at an early stage. The goal
of this research is to propose a system that measures the level of attentiveness in
real scenarios, and detects patterns of behavior associated to different attention
levels among different students. This system measures attention and uses this
information for training a decision support system that shows the level of attention
of a group of students in real time.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and
FCT – Fundação para a Ciência e Tecnologia within the Project Scope:
UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio
Evaluation of the Simulated Annealing and the Discrete Artificial Bee Colony in the Weight Tardiness Problem with Taguchi Experiments Parameterization

Meta-Heuristics (MH) are the most used optimization techniques to approach Complex Combinatorial Problems (COPs). Their ability to move beyond the local optimums make them an especially attractive choice to solve complex computational problems, such as most scheduling problems. However, the knowledge of what Meta-Heuristics perform better in certain problems is based on experiments. Classic MH, as the Simulated Annealing (SA) has been deeply studied, but newer MH, as the Discrete Artificial Bee Colony (DABC) still need to be examined in more detail. In this paper DABC has been compared with SA in 30 academic benchmark instances of the weighted tardiness problem (1 parallel to Sigma w(j)T(j)). Both MH parameters were fine-tuned with Taguchi Experiments. In the computational study DABC performed better and the subsequent statistical study demonstrated that DABC is more prone to find near-optimum solutions. On the other hand SA appeared to be more efficient.This work is supported by FEDER Funds through the "Programa Operacional Factores de Competitividade - COMPETE" program and by National Funds through FCT "Fundacao para a Ciencia e a Tecnologia" under the project: PEst-OE/EEI/UI0760/2014, and PEst2015-2020.info:eu-repo/semantics/publishedVersio
Industrial Plant Layout Analyzing Based on SNA

Social network analysis (SNA) is a widely studied research topics, which has been increasingly being applied for solving different kind of problems, including industrial manufacturing ones. This paper focuses on the application of SNA on an industrial plant layout problem. The study aims at analyzing the importance of using SNA techniques to analyze important relations between entities in a manufacturing environment, such as jobs and resources in the context of industrial plant layout analysis. The study carried out enabled to obtain relevant results for the identification of relations among these entities for supporting to establish an appropriate plant layout for producing the jobs.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - The Foundation for Science and Technology within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio
BigDimETL: ETL for multidimensional Big Data

With the broad range of data available on the World Wide Web and the increasing use of social media such as Facebook, Twitter, YouTube, etc. a “Big Data” notion has emerged. This latter has become an important aspect in nowadays business since it is full of important knowledge that is crucial for effective decision making. However, this kind of data brings with it new problems and challenges for the Decision Support System (DSS) that must be addressed. In this paper, we propose a new approach called BigDimETL (Big Dimensional ETL) that deals with ETL (Extract-Transform-Load) development process. Our approach focuses on integrating Big Data taking into account the MultiDimensional Structure (MDS) through a MapReduce paradigm
Developing an ambient intelligent-based decision support system for production and control planning

Scheduling production instructions in a manufacturing facility is key
to assure a efficient process that assures the desired product quantities are produced
in time, with quality and with the right resources. An efficient production
avoids the creation of downstream delays, and early completion which both can
be detrimental if storage space is limited and contracted quantities are important.
Therefore, the production, planning and control of manufacturing is increasingly
more difficult as family products increases. This paper presents an ongoing
Ambient Intelligent decision support system development that aims to provide
assistance on the creation on standard work procedures that assure production
quantity and efficiency by means of ambient intelligence, optimization heuristics
and machine learning in the context of a large organization.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT
- Fundac¸ ˜ao para a Ciˆencia e a Tecnologia (Portuguese Foundation for Science and Technology)
within the Project Scope UID/CEC/00319/2013. This research is also sponsored
by the Portugal Incentive System for Research and Technological Development.
Project in co-promotion no 002814/2015 (iFACTORY 2015-2018).info:eu-repo/semantics/publishedVersio
Review on Types of Root Failures in Shallow Landslides

Nowadays the interest of geotechnical engineers for green solutions is being developed and\ud
the use of vegetation as a reinforcement to improve slope stability is growing. The sliding\ud
surface of shallow landslides tends to not exceed 1.5–2 m depth, and as a consequence it\ud
can be crossed by roots that, in this case, work as a stabilizing measure. Therefore, the\ud
study of the soil-roots interaction is necessary to quantify the contribution of vegetation to\ud
the stability of shallow landslides. The goal of this paper is to provide an overview of the\ud
root failure mechanisms that can occur along the sliding surface and of the forces applied\ud
by roots, in order to evaluate the safety factor of a reinforced slope. Several prevailing\ud
stress states occur along a shallow landslide failure surface: tension stress at the slide crest,\ud
shear stresses along the base of the unstable soil layer and passive earth pressures at the\ud
slope toe. Some considerations are also made regarding acceptable simplifications, in terms\ud
of root geometry and soil-root friction strength, that are currently assumed in the literature
Psychophysical Evaluation of Audio Source Separation Methods

Source separation evaluation is typically a top-down process, starting with perceptual measures which capture fitness-for-purpose and followed by attempts to find physical (objective) measures that are predictive of the perceptual measures. In this paper, we take a contrasting bottom-up approach. We begin with the physical measures provided by the Blind Source Separation Evaluation Toolkit (BSS Eval) and we then look for corresponding perceptual correlates. This approach is known as psychophysics and has the distinct advantage of leading to interpretable, psychophysical models. We obtained perceptual similarity judgments from listeners in two experiments featuring vocal sources within musical mixtures. In the first experiment, listeners compared the overall quality of vocal signals estimated from musical mixtures using a range of competing source separation methods. In a loudness experiment, listeners compared the loudness balance of the competing musical accompaniment and vocal. Our preliminary results provide provisional validation of the psychophysical approac
Discriminative Enhancement for Single Channel Audio Source Separation using Deep Neural Networks

The sources separated by most single channel audio source separation techniques are usually distorted and each separated source contains residual signals from the other sources. To tackle this problem, we propose to enhance the separated sources to decrease the distortion and interference between the separated sources using deep neural networks (DNNs). Two different DNNs are used in this work. The first DNN is used to separate the sources from the mixed signal. The second DNN is used to enhance the separated signals. To consider the interactions between the separated sources, we propose to use a single DNN to enhance all the separated sources together. To reduce the residual signals of one source from the other separated sources (interference), we train the DNN for enhancement discriminatively to maximize the dissimilarity between the predicted sources. The experimental results show that using discriminative enhancement decreases the distortion and interference between the separated source
Retrieval, crawling and fusion of entity-centric data on the web

While the Web of (entity-centric) data has seen tremendous growth over the past years, take-up and re-use is still limited. Data vary heavily with respect to their scale, quality, coverage or dynamics, what poses challenges for tasks such as entity retrieval or search. This chapter provides an overview of approaches to deal with the increasing heterogeneity of Web data. On the one hand, recommendation, linking, profiling and retrieval can provide efficient means to enable discovery and search of entity-centric data, specifically when dealing with traditional knowledge graphs and linked data. On the other hand, embedded markup such as Microdata and RDFa has emerged a novel, Web-scale source of entitycentric knowledge. While markup has seen increasing adoption over the last few years, driven by initiatives such as schema.org, it constitutes an increasingly important source of entity-centric data on the Web, being in the same order of magnitude as the Web itself with regards to dynamics and scale. To this end, markup data lends itself as a data source for aiding tasks such as knowledge base augmentation, where data fusion techniques are required to address the inherent characteristics of markup data, such as its redundancy, heterogeneity and lack of links. Future directions are concerned with the exploitation of the complementary nature of markup data and traditional knowledge graphs.
The final publication is available at Springer via http://dx.doi.org/ 10.1007/978-3-319-53640-8_1
Topic detection in multichannel Italian newspapers

Nowadays, any person, company or public institution uses and exploits different channels to share private or public information with other people (friends, customers, relatives, etc.) or institutions. This context has changed the journalism, thus, the major newspapers report news not just on its own web site, but also on several social media such as Twitter or YouTube. The use of multiple communication media stimulates the need for integration and analysis of the content published globally and not just at the level of a single medium. An analysis to achieve a comprehensive overview of the information that reaches the end users and how they consume the information is needed. This analysis should identify the main topics in the news flow and reveal the mechanisms of publication of news on different media (e.g. news timeline). Currently, most of the work on this area is still focused on a single medium. So, an analysis across different media (channels) should improve the result of topic detection. This paper shows the application of a graph analytical approach, called Keygraph, to a set of very heterogeneous documents such as the news published on various media. A preliminary evaluation on the news published in a 5 days period was able to identify the main topics within the publications of a single newspaper, and also within the publications of 20 newspapers on several on-line channels