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 2018Show all

11 papers · 1 filter

cs.CL2018

Categorizing Comparative Sentences

Alexander Panchenko, Alexander Bondarenko, Mirco Franzek +2

We tackle the tasks of automatically identifying comparative sentences and categorizing the intended preference (e.g., "Python has better NLP libraries than MATLAB" => (Python, bet…

cs.CL2018

Sentiment Index of the Russian Speaking Facebook

Alexander Panchenko

A sentiment index measures the average emotional level in a corpus. We introduce four such indexes and use them to gauge average "positiveness" of a population during some period b…

cs.CL2018

Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction

Dmitry Ustalov, Alexander Panchenko, Chris Biemann +1

We present a detailed theoretical and computational analysis of the Watset meta-algorithm for fuzzy graph clustering, which has been found to be widely applicable in a variety of d…

cs.CL2018

Learning Graph Embeddings from WordNet-based Similarity Measures

Andrey Kutuzov, Mohammad Dorgham, Oleksiy Oliynyk +2

We present path2vec, a new approach for learning graph embeddings that relies on structural measures of pairwise node similarities. The model learns representations for nodes in a…

cs.CL2018

Unsupervised Semantic Frame Induction using Triclustering

Dmitry Ustalov, Alexander Panchenko, Andrei Kutuzov +2

We use dependency triples automatically extracted from a Web-scale corpus to perform unsupervised semantic frame induction. We cast the frame induction problem as a triclustering p…

cs.CL2018

How much does a word weigh? Weighting word embeddings for word sense induction

Nikolay Arefyev, Pavel Ermolaev, Alexander Panchenko

The paper describes our participation in the first shared task on word sense induction and disambiguation for the Russian language RUSSE'2018 (Panchenko et al., 2018). For each of…