Search Results for author: Tapio Salakoski

Found 26 papers, 5 papers with code

Multilingual is not enough: BERT for Finnish

1 code implementation15 Dec 2019 Antti Virtanen, Jenna Kanerva, Rami Ilo, Jouni Luoma, Juhani Luotolahti, Tapio Salakoski, Filip Ginter, Sampo Pyysalo

Deep learning-based language models pretrained on large unannotated text corpora have been demonstrated to allow efficient transfer learning for natural language processing, with recent approaches such as the transformer-based BERT model advancing the state of the art across a variety of tasks.

Dependency Parsing Named Entity Recognition +2

Is Multilingual BERT Fluent in Language Generation?

1 code implementation WS 2019 Samuel Rönnqvist, Jenna Kanerva, Tapio Salakoski, Filip Ginter

The multilingual BERT model is trained on 104 languages and meant to serve as a universal language model and tool for encoding sentences.

Language Modelling Text Generation

Template-free Data-to-Text Generation of Finnish Sports News

1 code implementation4 Oct 2019 Jenna Kanerva, Samuel Rönnqvist, Riina Kekki, Tapio Salakoski, Filip Ginter

News articles such as sports game reports are often thought to closely follow the underlying game statistics, but in practice they contain a notable amount of background knowledge, interpretation, insight into the game, and quotes that are not present in the official statistics.

Data-to-Text Generation News Generation

Leveraging Text Repetitions and Denoising Autoencoders in OCR Post-correction

no code implementations26 Jun 2019 Kai Hakala, Aleksi Vesanto, Niko Miekka, Tapio Salakoski, Filip Ginter

A common approach for improving OCR quality is a post-processing step based on models correcting misdetected characters and tokens.

Denoising Optical Character Recognition

Universal Lemmatizer: A Sequence to Sequence Model for Lemmatizing Universal Dependencies Treebanks

no code implementations3 Feb 2019 Jenna Kanerva, Filip Ginter, Tapio Salakoski

We evaluate our lemmatizer on 52 different languages and 76 different treebanks, showing that our system outperforms all latest baseline systems.

Data Augmentation Lemmatization

Evaluation of a Prototype System that Automatically Assigns Subject Headings to Nursing Narratives Using Recurrent Neural Network

no code implementations WS 2018 Hans Moen, Kai Hakala, Laura-Maria Peltonen, Henry Suhonen, Petri Loukasm{\"a}ki, Tapio Salakoski, Filip Ginter, Sanna Salanter{\"a}

Our aim is to allow nurses to write in a narrative manner without having to plan and structure the text with respect to sections and subject headings, instead the system should assist with the assignment of subject headings and restructuring afterwards.

Text Classification

Biomedical Event Extraction Using Convolutional Neural Networks and Dependency Parsing

no code implementations WS 2018 Jari Bj{\"o}rne, Tapio Salakoski

Using this system, our machine learning model can be easily applied to a large set of corpora from e. g. the BioNLP, DDI Extraction and BioCreative shared tasks.

Dependency Parsing NER +3

End-to-End System for Bacteria Habitat Extraction

1 code implementation WS 2017 Farrokh Mehryary, Kai Hakala, Suwisa Kaewphan, Jari Bj{\"o}rne, Tapio Salakoski, Filip Ginter

The official evaluation shows that the joint performance of our entity detection and relation extraction models outperforms the winning team of the Shared Task by 19pp on F1-score, establishing a new top score for the task.

Named Entity Recognition Relation Extraction

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

1 code implementation3 Jan 2016 Yuxiang Jiang, Tal Ronnen Oron, Wyatt T Clark, Asma R Bankapur, Daniel D'Andrea, Rosalba Lepore, Christopher S Funk, Indika Kahanda, Karin M Verspoor, Asa Ben-Hur, Emily Koo, Duncan Penfold-Brown, Dennis Shasha, Noah Youngs, Richard Bonneau, Alexandra Lin, Sayed ME Sahraeian, Pier Luigi Martelli, Giuseppe Profiti, Rita Casadio, Renzhi Cao, Zhaolong Zhong, Jianlin Cheng, Adrian Altenhoff, Nives Skunca, Christophe Dessimoz, Tunca Dogan, Kai Hakala, Suwisa Kaewphan, Farrokh Mehryary, Tapio Salakoski, Filip Ginter, Hai Fang, Ben Smithers, Matt Oates, Julian Gough, Petri Törönen, Patrik Koskinen, Liisa Holm, Ching-Tai Chen, Wen-Lian Hsu, Kevin Bryson, Domenico Cozzetto, Federico Minneci, David T Jones, Samuel Chapman, Dukka B K. C., Ishita K Khan, Daisuke Kihara, Dan Ofer, Nadav Rappoport, Amos Stern, Elena Cibrian-Uhalte, Paul Denny, Rebecca E Foulger, Reija Hieta, Duncan Legge, Ruth C Lovering, Michele Magrane, Anna N Melidoni, Prudence Mutowo-Meullenet, Klemens Pichler, Aleksandra Shypitsyna, Biao Li, Pooya Zakeri, Sarah ElShal, Léon-Charles Tranchevent, Sayoni Das, Natalie L Dawson, David Lee, Jonathan G Lees, Ian Sillitoe, Prajwal Bhat, Tamás Nepusz, Alfonso E Romero, Rajkumar Sasidharan, Haixuan Yang, Alberto Paccanaro, Jesse Gillis, Adriana E Sedeño-Cortés, Paul Pavlidis, Shou Feng, Juan M Cejuela, Tatyana Goldberg, Tobias Hamp, Lothar Richter, Asaf Salamov, Toni Gabaldon, Marina Marcet-Houben, Fran Supek, Qingtian Gong, Wei Ning, Yuanpeng Zhou, Weidong Tian, Marco Falda, Paolo Fontana, Enrico Lavezzo, Stefano Toppo, Carlo Ferrari, Manuel Giollo, Damiano Piovesan, Silvio Tosatto, Angela del Pozo, José M Fernández, Paolo Maietta, Alfonso Valencia, Michael L Tress, Alfredo Benso, Stefano Di Carlo, Gianfranco Politano, Alessandro Savino, Hafeez Ur Rehman, Matteo Re, Marco Mesiti, Giorgio Valentini, Joachim W Bargsten, Aalt DJ van Dijk, Branislava Gemovic, Sanja Glisic, Vladmir Perovic, Veljko Veljkovic, Nevena Veljkovic, Danillo C Almeida-e-Silva, Ricardo ZN Vencio, Malvika Sharan, Jörg Vogel, Lakesh Kansakar, Shanshan Zhang, Slobodan Vucetic, Zheng Wang, Michael JE Sternberg, Mark N Wass, Rachael P Huntley, Maria J Martin, Claire O'Donovan, Peter N. Robinson, Yves Moreau, Anna Tramontano, Patricia C Babbitt, Steven E Brenner, Michal Linial, Christine A Orengo, Burkhard Rost, Casey S Greene, Sean D Mooney, Iddo Friedberg, Predrag Radivojac

To review progress in the field, the analysis also compared the best methods participating in CAFA1 to those of CAFA2.

Quantitative Methods

Cannot find the paper you are looking for? You can Submit a new open access paper.