Hajime Morita


2021

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Learning Entity-Likeness with Multiple Approximate Matches for Biomedical NER
An Nguyen Le | Hajime Morita | Tomoya Iwakura
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)

Biomedical Named Entities are complex, so approximate matching has been used to improve entity coverage. However, the usual approximate matching approach fetches only one matching result, which is often noisy. In this work, we propose a method for biomedical NER that fetches multiple approximate matches for a given phrase to leverage their variations to estimate entity-likeness. The model uses pooling to discard the unnecessary information from the noisy matching results, and learn the entity-likeness of the phrase with multiple approximate matches. Experimental results on three benchmark datasets from the biomedical domain, BC2GM, NCBI-disease, and BC4CHEMD, demonstrate the effectiveness. Our model improves the average by up to +0.21 points compared to a BioBERT-based NER.

2019

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A Fast and Accurate Partially Deterministic Morphological Analysis
Hajime Morita | Tomoya Iwakura
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)

This paper proposes a partially deterministic morphological analysis method for improved processing speed. Maximum matching is a fast deterministic method for morphological analysis. However, the method tends to decrease performance due to lack of consideration of contextual information. In order to use maximum matching safely, we propose the use of Context Independent Strings (CISs), which are strings that do not have ambiguity in terms of morphological analysis. Our method first identifies CISs in a sentence using maximum matching without contextual information, then analyzes the unprocessed part of the sentence using a bi-gram-based morphological analysis model. We evaluate the method on a Japanese morphological analysis task. The experimental results show a 30% reduction of running time while maintaining improved accuracy.

2017

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Automatically Acquired Lexical Knowledge Improves Japanese Joint Morphological and Dependency Analysis
Daisuke Kawahara | Yuta Hayashibe | Hajime Morita | Sadao Kurohashi
Proceedings of the 15th International Conference on Parsing Technologies

This paper presents a joint model for morphological and dependency analysis based on automatically acquired lexical knowledge. This model takes advantage of rich lexical knowledge to simultaneously resolve word segmentation, POS, and dependency ambiguities. In our experiments on Japanese, we show the effectiveness of our joint model over conventional pipeline models.

2015

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Morphological Analysis for Unsegmented Languages using Recurrent Neural Network Language Model
Hajime Morita | Daisuke Kawahara | Sadao Kurohashi
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

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Surrounding Word Sense Model for Japanese All-words Word Sense Disambiguation
Kanako Komiya | Yuto Sasaki | Hajime Morita | Minoru Sasaki | Hiroyuki Shinnou | Yoshiyuki Kotani
Proceedings of the 29th Pacific Asia Conference on Language, Information and Computation

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Classification and Acquisition of Contradictory Event Pairs using Crowdsourcing
Yu Takabatake | Hajime Morita | Daisuke Kawahara | Sadao Kurohashi | Ryuichiro Higashinaka | Yoshihiro Matsuo
Proceedings of the The 3rd Workshop on EVENTS: Definition, Detection, Coreference, and Representation

2013

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Subtree Extractive Summarization via Submodular Maximization
Hajime Morita | Ryohei Sasano | Hiroya Takamura | Manabu Okumura
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

2011

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Query Snowball: A Co-occurrence-based Approach to Multi-document Summarization for Question Answering
Hajime Morita | Tetsuya Sakai | Manabu Okumura
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

2009

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Structured Output Learning with Polynomial Kernel
Hajime Morita | Hiroya Takamura | Manabu Okumura
Proceedings of the International Conference RANLP-2009