activity
20192026
most citedGLocal-K: Global and Local Kernels for Recommender Systems

41 citations · 225 across the 43 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.CL2023

Re-Temp: Relation-Aware Temporal Representation Learning for Temporal Knowledge Graph Completion

Kunze Wang, Soyeon Caren Han, Josiah Poon

Temporal Knowledge Graph Completion (TKGC) under the extrapolation setting aims to predict the missing entity from a fact in the future, posing a challenge that aligns more closely…

cs.CL2023

MC-DRE: Multi-Aspect Cross Integration for Drug Event/Entity Extraction

Jie Yang, Soyeon Caren Han, Siqu Long +2

Extracting meaningful drug-related information chunks, such as adverse drug events (ADE), is crucial for preventing morbidity and saving many lives. Most ADEs are reported via an u…

cs.SI2023★ 23 cited

Social network modeling and applications, a tutorial

Lisette Espín-Noboa, Tiago Peixoto, Fariba Karimi

Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performanc…

cs.CL2023

Tri-level Joint Natural Language Understanding for Multi-turn Conversational Datasets

Henry Weld, Sijia Hu, Siqu Long +2

Natural language understanding typically maps single utterances to a dual level semantic frame, sentence level intent and slot labels at the word level. The best performing models…

cs.IR2023★ 3 cited

SimCGNN: Simple Contrastive Graph Neural Network for Session-based Recommendation

Yuan Cao, Xudong Zhang, Fan Zhang +5

Session-based recommendation (SBR) problem, which focuses on next-item prediction for anonymous users, has received increasingly more attention from researchers. Existing graph-bas…

cs.CL2023★ 5 cited

StockEmotions: Discover Investor Emotions for Financial Sentiment Analysis and Multivariate Time Series

Jean Lee, Hoyoul Luis Youn, Josiah Poon +1

There has been growing interest in applying NLP techniques in the financial domain, however, resources are extremely limited. This paper introduces StockEmotions, a new dataset for…