Leveraging multilingual descriptions for link prediction: Initial experiments

In most Knowledge Graphs (KGs), textual descriptions ofentities are provided in multiple natural languages. Additional informa-tion that is not explicitly represented in the structured part of the KGmight be available in these textual descriptions. Link prediction modelswhich make use of entity descriptions usually consider only one language.However, descriptions given in multiple languages may provide comple-mentary information which should be taken into consideration for thetasks such as link prediction. In this poster paper, the benefits of mul-tilingual embeddings for incorporating multilingual entity descriptionsinto the task of link prediction in KGs are investigate

Migranalytics: Entity-based analytics of migration tweets

This poster focuses on a visual analysis of the tweets related to European migration crisis. It uses TweetsKB as a starting point and then formulates a search criteria for extracting tweets by enriching semantic entities and hashtags starting from the seed word \Refugee". It combines European migration statistics with the information obtained by the tweets and provides visual analysis from different perspectives

A knowledge graph embeddings based approach for author name disambiguation using literals

Scholarly data is growing continuously containing information about the articles from a plethora of venues including conferences, journals, etc. Many initiatives have been taken to make scholarly data available in the form of Knowledge Graphs (KGs). These efforts to standardize these data and make them accessible have also led to many challenges such as exploration of scholarly articles, ambiguous authors, etc. This study more specifically targets the problem of Author Name Disambiguation (AND) on Scholarly KGs and presents a novel framework, Literally Author Name Disambiguation (LAND), which utilizes Knowledge Graph Embeddings (KGEs) using multimodal literal information generated from these KGs. This framework is based on three components: (1) multimodal KGEs, (2) a blocking procedure, and finally, (3) hierarchical Agglomerative Clustering. Extensive experiments have been conducted on two newly created KGs: (i) KG containing information from Scientometrics Journal from 1978 onwards (OC-782K), and (ii) a KG extracted from a well-known benchmark for AND provided by AMiner (AMiner-534K). The results show that our proposed architecture outperforms our baselines of 8–14% in terms of F1 score and shows competitive performances on a challenging benchmark such as AMiner. The code and the datasets are publicly available through Github (https://github.com/sntcristian/and-kge) and Zenodo (https://doi.org/10.5281/zenodo.6309855) respectively

Temporal Evolution of the Migration-related Topics on Social Media?

This poster focuses on capturing the temporal evolution of migration-related topics on relevant tweets. It uses Dynamic Embedded Topic Model (DETM) as a learning algorithm to perform a quantitative and qualitative analysis of these emerging topics. TweetsKB is extended with the extracted Twitter dataset along with the results of DETM which considers temporality. These results are then further analyzed and visualized. It reveals that the trajectories of the migration-related topics are in agreement with historical events

Strong-coupling effects in the relaxation dynamics of ultracold neutral plasmas

We describe a hybrid molecular dynamics approach for the description of ultracold neutral plasmas, based on an adiabatic treatment of the electron gas and a full molecular dynamics simulation of the ions, which allows us to follow the long-time evolution of the plasma including the effect of the strongly coupled ion motion. The plasma shows a rather complex relaxation behavior, connected with temporal as well as spatial oscillations of the ion temperature. Furthermore, additional laser cooling of the ions during the plasma evolution drastically modifies the expansion dynamics, so that crystallization of the ion component can occur in this nonequilibrium system, leading to lattice-like structures or even long-range order resulting in concentric shells

The Quantum Mellin transform

We uncover a new type of unitary operation for quantum mechanics on the half-line which yields a transformation to ``Hyperbolic phase space''. We show that this new unitary change of basis from the position x on the half line to the Hyperbolic momentum $p_\eta$, transforms the wavefunction via a Mellin transform on to the critial line $s=1/2-ip_\eta$. We utilise this new transform to find quantum wavefunctions whose Hyperbolic momentum representation approximate a class of higher transcendental functions, and in particular, approximate the Riemann Zeta function. We finally give possible physical realisations to perform an indirect measurement of the Hyperbolic momentum of a quantum system on the half-line.Comment: 23 pages, 6 Figure

In-medium modifications of the ππ\pi\pi interaction in photon-induced reactions

Differential cross sections of the reactions $(\gamma,\pi^\circ\pi^\circ)$ and $(\gamma,\pi^\circ\pi^++\pi^\circ\pi^-)$ have been measured for several nuclei ($^1$H,$^{12}$C, and $^{\rm nat}$Pb) at an incident-photon energy of $E_{\gamma}$=400-460 MeV at the tagged-photon facility at MAMI-B using the TAPS spectrometer. A significant nuclear-mass dependence of the $\pi\pi$ invariant-mass distribution is found in the $\pi^\circ\pi^\circ$ channel. This dependence is not observed in the $\pi^\circ\pi^{+/-}$ channel and is consistent with an in-medium modification of the $\pi\pi$ interaction in the $I$=$J$=0 channel. The data are compared to $\pi$-induced measurements and to calculations within a chiral-unitary approach