activity
20132021
most citedMaking Sense of Word Embeddings

15 citations · 42 across the 11 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

cs.SI20197 cited

Large-Scale Parallel Matching of Social Network Profiles

Alexander Panchenko, Dmitry Babaev, Sergei Obiedkov

A profile matching algorithm takes as input a user profile of one social network and returns, if existing, the profile of the same person in another social network. Such methods ha…

cs.CL2019

Making Fast Graph-based Algorithms with Graph Metric Embeddings

Andrey Kutuzov, Mohammad Dorgham, Oleksiy Oliynyk +2

The computation of distance measures between nodes in graphs is inefficient and does not scale to large graphs. We explore dense vector representations as an effective way to appro…

cs.CL2019

On the Compositionality Prediction of Noun Phrases using Poincaré Embeddings

Abhik Jana, Dmitry Puzyrev, Alexander Panchenko +3

The compositionality degree of multiword expressions indicates to what extent the meaning of a phrase can be derived from the meaning of its constituents and their grammatical rela…

cs.CL2019

Every child should have parents: a taxonomy refinement algorithm based on hyperbolic term embeddings

Rami Aly, Shantanu Acharya, Alexander Ossa +3

We introduce the use of Poincaré embeddings to improve existing state-of-the-art approaches to domain-specific taxonomy induction from text as a signal for both relocating wrong hy…

cs.CL2019

HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings

Saba Anwar, Dmitry Ustalov, Nikolay Arefyev +3

We present our system for semantic frame induction that showed the best performance in Subtask B.1 and finished as the runner-up in Subtask A of the SemEval 2019 Task 2 on unsuperv…

cs.CL201914 cited

Answering Comparative Questions: Better than Ten-Blue-Links?

Matthias Schildwächter, Alexander Bondarenko, Julian Zenker +3

We present CAM (comparative argumentative machine), a novel open-domain IR system to argumentatively compare objects with respect to information extracted from the Common Crawl. In…