Kateryna Tymoshenko


2018

pdf bib
Cross-Pair Text Representations for Answer Sentence Selection
Kateryna Tymoshenko | Alessandro Moschitti
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

High-level semantics tasks, e.g., paraphrasing, textual entailment or question answering, involve modeling of text pairs. Before the emergence of neural networks, this has been mostly performed using intra-pair features, which incorporate similarity scores or rewrite rules computed between the members within the same pair. In this paper, we compute scalar products between vectors representing similarity between members of different pairs, in place of simply using a single vector for each pair. This allows us to obtain a representation specific to any pair of pairs, which delivers the state of the art in answer sentence selection. Most importantly, our approach can outperform much more complex algorithms based on neural networks.

2017

pdf bib
RelTextRank: An Open Source Framework for Building Relational Syntactic-Semantic Text Pair Representations
Kateryna Tymoshenko | Alessandro Moschitti | Massimo Nicosia | Aliaksei Severyn
Proceedings of ACL 2017, System Demonstrations

pdf bib
Ranking Kernels for Structures and Embeddings: A Hybrid Preference and Classification Model
Kateryna Tymoshenko | Daniele Bonadiman | Alessandro Moschitti
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Recent work has shown that Tree Kernels (TKs) and Convolutional Neural Networks (CNNs) obtain the state of the art in answer sentence reranking. Additionally, their combination used in Support Vector Machines (SVMs) is promising as it can exploit both the syntactic patterns captured by TKs and the embeddings learned by CNNs. However, the embeddings are constructed according to a classification function, which is not directly exploitable in the preference ranking algorithm of SVMs. In this work, we propose a new hybrid approach combining preference ranking applied to TKs and pointwise ranking applied to CNNs. We show that our approach produces better results on two well-known and rather different datasets: WikiQA for answer sentence selection and SemEval cQA for comment selection in Community Question Answering.

2016

pdf bib
Convolutional Neural Networks vs. Convolution Kernels: Feature Engineering for Answer Sentence Reranking
Kateryna Tymoshenko | Daniele Bonadiman | Alessandro Moschitti
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

pdf bib
Semi-supervised Question Retrieval with Gated Convolutions
Tao Lei | Hrishikesh Joshi | Regina Barzilay | Tommi Jaakkola | Kateryna Tymoshenko | Alessandro Moschitti | Lluís Màrquez
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

pdf bib
ConvKN at SemEval-2016 Task 3: Answer and Question Selection for Question Answering on Arabic and English Fora
Alberto Barrón-Cedeño | Daniele Bonadiman | Giovanni Da San Martino | Shafiq Joty | Alessandro Moschitti | Fahad Al Obaidli | Salvatore Romeo | Kateryna Tymoshenko | Antonio Uva
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

2014

pdf bib
Encoding Semantic Resources in Syntactic Structures for Passage Reranking
Kateryna Tymoshenko | Alessandro Moschitti | Aliaksei Severyn
Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics

pdf bib
Towards Model Driven Architectures for Human Language Technologies
Alessandro Di Bari | Guido Vetere | Kateryna Tymoshenko
Proceedings of the Workshop on Open Infrastructures and Analysis Frameworks for HLT

2010

pdf bib
Extending English ACE 2005 Corpus Annotation with Ground-truth Links to Wikipedia
Luisa Bentivogli | Pamela Forner | Claudio Giuliano | Alessandro Marchetti | Emanuele Pianta | Kateryna Tymoshenko
Proceedings of the 2nd Workshop on The People’s Web Meets NLP: Collaboratively Constructed Semantic Resources

pdf bib
Identifying and Ranking Topic Clusters in the Blogosphere
M. Atif Qureshi | Arjumand Younus | Muhammad Saeed | Nasir Touheed | Emanuele Pianta | Kateryna Tymoshenko
Proceedings of the 2nd Workshop on The People’s Web Meets NLP: Collaboratively Constructed Semantic Resources

pdf bib
FBK-IRST: Semantic Relation Extraction Using Cyc
Kateryna Tymoshenko | Claudio Giuliano
Proceedings of the 5th International Workshop on Semantic Evaluation