Carolyn Penstein Rosé · PaperMetrix

A Supervised Approach to Predict Company Acquisition with Factual and Topic Features Using Profiles and News Articles on TechCrunch

2021 · Proceedings of the International AAAI Conference on Web and Social Media

Merger and Acquisition (M&A) prediction has been an interesting and challenging research topic in the past a few decades. However, past work has only adopted numerical features in building models, and yet the valuable textual …

Using Machine Learning Techniques to Analyze and Support Mediation of Student E-Discussions

2018 · INDIGO (University of Illinois at Chicago)

Students are starting to use networked visual argumentation tools to discuss, debate, and argue with one another about topics presented by a teacher. However, this development gives rise to an emergent issue for teachers: how …

Linguistic Markers of Influence in Informal Interactions

2017

There has been a long standing interest in understanding 'Social Influence' both in Social Sciences and in Computational Linguistics. In this paper, we present a novel approach to study and measure interpersonal influence in daily …

STAGE: Tool for Automated Extraction of Semantic Time Cues to Enrich Neural Temporal Ordering Models

2021 · arXiv (Cornell University)

Despite achieving state-of-the-art accuracy on temporal ordering of events, neural models showcase significant gaps in performance. Our work seeks to fill one of these gaps by leveraging an under-explored dimension of textual semantics: rich semantic …

Robust Knowledge Graph Completion with Stacked Convolutions and a Student Re-Ranking Network

2021

Knowledge Graph (KG) completion research usually focuses on densely connected benchmark datasets that are not representative of real KGs. We curate two KG datasets that include biomedical and encyclopedic knowledge and use an existing commonsense …

PerKGQA: Question Answering over Personalized Knowledge Graphs

2022 · Findings of the Association for Computational Linguistics: NAACL 2022

Previous studies on question answering over knowledge graphs have typically operated over a single knowledge graph (KG). This KG is assumed to be known a priori and is leveraged similarly for all users' queries during …

Exploring Numeracy in Word Embeddings

2019

Word embeddings are now pervasive across NLP subfields as the de-facto method of forming text representataions. In this work, we show that existing embedding models are inadequate at constructing representations that capture salient aspects of …