A brief overview of universal sentence representation methods: A linguistic view

R Li, X Zhao, MF Moens - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
How to transfer the semantic information in a sentence to a computable numerical
embedding form is a fundamental problem in natural language processing. An informative …

Pseudo-relevance feedback for multiple representation dense retrieval

X Wang, C Macdonald, N Tonellotto… - Proceedings of the 2021 …, 2021 - dl.acm.org
Pseudo-relevance feedback mechanisms, from Rocchio to the relevance models, have
shown the usefulness of expanding and reweighting the users' initial queries using …

ColBERT-PRF: Semantic pseudo-relevance feedback for dense passage and document retrieval

X Wang, C Macdonald, N Tonellotto… - ACM Transactions on the …, 2023 - dl.acm.org
Pseudo-relevance feedback mechanisms, from Rocchio to the relevance models, have
shown the usefulness of expanding and reweighting the users' initial queries using …

Deep learning–based named entity recognition and resolution of referential ambiguities for enhanced information extraction from construction safety regulations

X Wang, N El-Gohary - Journal of Computing in Civil Engineering, 2023 - ascelibrary.org
Construction safety regulations and standards contain a massive number of fall protection
requirements with respect to different equipment, facilities, and operations. Automated field …

Deep-qpp: A pairwise interaction-based deep learning model for supervised query performance prediction

S Datta, D Ganguly, D Greene, M Mitra - … on web search and data mining, 2022 - dl.acm.org
Motivated by the recent success of end-to-end deep neural models for ranking tasks, we
present here a supervised end-to-end neural approach for query performance prediction …

Automatic document screening of medical literature using word and text embeddings in an active learning setting

A Carvallo, D Parra, H Lobel, A Soto - Scientometrics, 2020 - Springer
Document screening is a fundamental task within Evidence-based Medicine (EBM), a
practice that provides scientific evidence to support medical decisions. Several approaches …

A literature embedding model for cardiovascular disease prediction using risk factors, symptoms, and genotype information

J Moon, HF Posada-Quintero, KH Chon - Expert Systems with Applications, 2023 - Elsevier
Accurate prediction of cardiovascular disease (CVD) requires multifaceted information
consisting of not only a patient's medical history, but genomic data, symptoms, lifestyle, and …

Dimension importance estimation for dense information retrieval

G Faggioli, N Ferro, R Perego… - Proceedings of the 47th …, 2024 - dl.acm.org
Recent advances in Information Retrieval have shown the effectiveness of embedding
queries and documents in a latent high-dimensional space to compute their similarity. While …

[PDF][PDF] Social media sentiment analysis using convolutional neural network (CNN) dan gated recurrent unit (GRU)

AZR Adam, EB Setiawan - Jurnal Ilmiah Teknik Elektro Komputer …, 2023 - researchgate.net
The advancing technologies are aimed to maximize human performance. One of the great
developments in technology is social media. The social media used in this study is Twitter …

A hybrid query expansion framework for the optimal retrieval of the biomedical literature

S Malik, U Shoaib, SAC Bukhari, H El Sayed, MA Khan - Smart Health, 2022 - Elsevier
With the proliferation of biomedical literature, it is quite challenging for biomedical scientists
to keep them updated with the new advancements. In biomedical literature retrieval systems …