no code implementations • 20 Sep 2023 • Yuan An, Jane Greenberg, Alex Kalinowski, Xintong Zhao, Xiaohua Hu, Fernando J. Uribe-Romo, Kyle Langlois, Jacob Furst, Diego A. Gómez-Gualdrón
To evaluate the benchmark, we have developed a systematic approach for utilizing ChatGPT to translate natural language questions into formal KG queries.
1 code implementation • 22 Aug 2022 • Alexander Kalinowski, Yuan An
The majority of knowledge graph embedding techniques treat entities and predicates as separate embedding matrices, using aggregation functions to build a representation of the input triple.
no code implementations • 22 Jul 2022 • Yuan An, Alex Kalinowski, Jane Greenberg
Measuring the distance between ontological elements is fundamental for ontology matching.
no code implementations • 10 Jul 2022 • Yuan An, Jane Greenberg, Xintong Zhao, Xiaohua Hu, Scott McCLellan, Alex Kalinowski, Fernando J. Uribe-Romo, Kyle Langlois, Jacob Furst, Diego A. Gómez-Gualdrón, Fernando Fajardo-Rojas, Katherine Ardila
Metal-Organic Frameworks (MOFs) are a class of modular, porous crystalline materials that have great potential to revolutionize applications such as gas storage, molecular separations, chemical sensing, catalysis, and drug delivery.
1 code implementation • 2 Oct 2021 • Yuan An, Alexander Kalinowski, Jane Greenberg
Sentence embedding methods offer a powerful approach for working with short textual constructs or sequences of words.
no code implementations • 1 Jul 2021 • Wei Dai, Yuan An, Wen Long
Through in-depth analysis of ultra high frequency (UHF) stock price change data, more reasonable discrete dynamic distribution models are constructed in this paper.
no code implementations • 26 Oct 2020 • Alexander Kalinowski, Yuan An
Neural embedding approaches have become a staple in the fields of computer vision, natural language processing, and more recently, graph analytics.
1 code implementation • 23 Sep 2020 • Alexander Kalinowski, Yuan An
Although a number of techniques have been proposed in the literature for embedding both sentences and knowledge graphs, little is known about the structural and semantic properties of these embedding spaces in terms of relation extraction.
no code implementations • WS 2017 • Yuan Ling, Yuan An, Sadid Hasan
This paper presents a novel approach to the task of automatically inferring the most probable diagnosis from a given clinical narrative.