Qing Ma


2016

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Retrieval Term Prediction Using Deep Learning Methods
Qing Ma | Ibuki Tanigawa | Masaki Murata
Proceedings of the 30th Pacific Asia Conference on Language, Information and Computation: Posters

2014

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Retrieval Term Prediction Using Deep Belief Networks
Qing Ma | Ibuki Tanigawa | Masaki Murata
Proceedings of the 28th Pacific Asia Conference on Language, Information and Computing

2011

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Extraction of Broad-Scale, High-Precision Japanese-English Parallel Translation Expressions Using Lexical Information and Rules
Qing Ma | Shinya Sakagami | Masaki Murata
Proceedings of the 25th Pacific Asia Conference on Language, Information and Computation

2008

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Non-Factoid Japanese Question Answering through Passage Retrieval that Is Weighted Based on Types of Answers
Masaki Murata | Sachiyo Tsukawaki | Toshiyuki Kanamaru | Qing Ma | Hitoshi Isahara
Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-II

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Word Alignment Annotation in a Japanese-Chinese Parallel Corpus
Yujie Zhang | Zhulong Wang | Kiyotaka Uchimoto | Qing Ma | Hitoshi Isahara
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

Parallel corpora are critical resources for machine translation research and development since parallel corpora contain translation equivalences of various granularities. Manual annotation of word & phrase alignment is of significance to provide gold-standard for developing and evaluating both example-based machine translation model and statistical machine translation model. This paper presents the work of word & phrase alignment annotation in the NICT Japanese-Chinese parallel corpus, which is constructed at the National Institute of Information and Communications Technology (NICT). We describe the specification of word alignment annotation and the tools specially developed for the manual annotation. The manual annotation on 17,000 sentence pairs has been completed. We examined the manually annotated word alignment data and extracted translation knowledge from the word & phrase aligned corpus.

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Selection of Japanese-English Equivalents by Integrating High-quality Corpora and Huge Amounts of Web Data
Qing Ma | Koichi Nakao | Masaki Murata | Hitoshi Isahara
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

As a first step to developing systems that enable non-native speakers to output near-perfect English sentences for given mixed English-Japanese sentences, we propose new approaches for selecting English equivalents by using the number of hits for various contexts in large English corpora. As the large English corpora, we not only used the huge amounts of Web data but also the manually compiled large, high-quality English corpora. Using high-quality corpora enables us to accurately select equivalents, and using huge amounts of Web data enables us to resolve the problem of the shortage of hits that normally occurs when using only high-quality corpora. The types and lengths of contexts used to select equivalents are variable and optimally determined according to the number of hits in the corpora, so that performance can be further refined. Computer experiments showed that the precision of our methods was much higher than that of the existing methods for equivalent selection.

2007

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Building Japanese-Chinese translation dictionary based on EDR Japanese-English bilingual dictionary
Yujie Zhang | Qing Ma | Hitoshi Isahara
Proceedings of Machine Translation Summit XI: Papers

2006

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Semantic Analysis of Abstract Nouns to Compile a Thesaurus of Adjectives
Kyoko Kanzaki | Qing Ma | Eiko Yamamoto | Hitoshi Isahara
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

Aiming to compile a thesaurus of adjectives, we discuss how to extract abstract nouns categorizing adjectives, clarify the semantic and syntactic functions of these abstract nouns, and manually evaluate the capability to extract the “instance-category” relations. We focused on some Japanese syntactic structures and utilized possibility of omission of abstract noun to decide whether or not a semantic relation between an adjective and an abstract noun is an “instance-category” relation. For 63% of the adjectives (57 groups/90 groups) in our experiments, our extracted categories were found to be most suitable. For 22 % of the adjectives (20/90), the categories in the EDR lexicon were found to be most suitable. For 14% of the adjectives (13/90), neither our extracted categories nor those in EDR were found to be suitable, or examinees’ own categories were considered to be more suitable. From our experimental results, we found that the correspondence between a group of adjectives and their category name was more suitable in our method than in the EDR lexicon.

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Development of an Automatic Trend Exploration System using the MuST Data Collection
Masaki Murata | Koji Ichii | Qing Ma | Tamotsu Shirado | Toshiyuki Kanamaru | Sachiyo Tsukawaki | Hitoshi Isahara
Proceedings of the Workshop on Information Extraction Beyond The Document

2005

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Building an Annotated Japanese-Chinese Parallel Corpus - A Part of NICT Multilingual Corpora
Yujie Zhang | Kiyotaka Uchimoto | Qing Ma | Hitoshi Isahara
Companion Volume to the Proceedings of Conference including Posters/Demos and tutorial abstracts

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Information Retrieval Capable of Visualization and High Precision
Qing Ma | Kousuke Enomoto | Masaki Murata | Hitoshi Isahara
Companion Volume to the Proceedings of Conference including Posters/Demos and tutorial abstracts

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Trend Survey on Japanese Natural Language Processing Studies over the Last Decade
Masaki Murata | Koji Ichii | Qing Ma | Tamotsu Shirado | Toshiyuki Kanamaru | Hitoshi Isahara
Companion Volume to the Proceedings of Conference including Posters/Demos and tutorial abstracts

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Analysis of Machine Translation Systems’ Errors in Tense, Aspect, and Modality
Masaki Murata | Kiyotaka Uchimoto | Qing Ma | Toshiyuki Kanamaru | Hitoshi Isahara
Proceedings of the 19th Pacific Asia Conference on Language, Information and Computation

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Building an Annotated Japanese-Chinese Parallel Corpus – A Part of NICT Multilingual Corpora
Yujie Zhang | Kiyotaka Uchimoto | Qing Ma | Hitoshi Isahara
Proceedings of Machine Translation Summit X: Papers

We are constricting a Japanese-Chinese parallel corpus, which is a part of the NICT Multilingual Corpora. The corpus is general domain, of large scale of about 40,000 sentence pairs, long sentences, annotated with detailed information and high quality. To the best of our knowledge, this will be the first annotated Japanese-Chinese parallel corpus in the world. We created the corpus by selecting Japanese sentences from Mainichi Newspaper and then manually translating them into Chinese. We then annotated the corpus with morphological and syntactic structures and alignments at word and phrase levels. This paper describes the specification in human translation and detailed information annotation, and the tools we developed in the project. The experience we obtained and points we paid special attentions are also introduced for share with other researches in corpora construction.

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A Multi-aligner for Japanese-Chinese Parallel Corpora
Yujie Zhang | Qun Liu | Qing Ma | Hitoshi Isahara
Proceedings of Machine Translation Summit X: Papers

Automatic word alignment is an important technology for extracting translation knowledge from parallel corpora. However, automatic techniques cannot resolve this problem completely because of variances in translations. We therefore need to investigate the performance potential of automatic word alignment and then decide how to suitably apply it. In this paper we first propose a lexical knowledge-based approach to word alignment on a Japanese-Chinese corpus. Then we evaluate the performance of the proposed approach on the corpus. At the same time we also apply a statistics-based approach, the well-known toolkit GIZA++, to the same test data. Through comparison of the performances of the two approaches, we propose a multi-aligner, exploiting the lexical knowledge-based aligner and the statistics-based aligner at the same time. Quantitative results confirmed the effectiveness of the multi-aligner.

2004

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Extraction of Hyperonymy of Adjectives from Large Corpora by Using the Neural Network Model
Kyoko Kanzaki | Qing Ma | Eiko Yamamoto | Masaki Murata | Hitoshi Isahara
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

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Construction of an Objective Hierarchy of Abstract Concepts via Directional Similarity
Kyoko Kanzaki | Eiko Yamamoto | Qing Ma | Hitoshi Isahara
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics

2003

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Semantic Maps for Word Alignment in Bilingual Parallel Corpora
Qing Ma | Yujie Zhang | Masaki Murata | Hitoshi Isahara
Proceedings of the Second SIGHAN Workshop on Chinese Language Processing

2002

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Correction of errors in a modality corpus used for machine translation using machine-learning
Masaki Murata | Masao Utiyama | Kiyotaka Uchimoto | Qing Ma | Hitoshi Isahara
Proceedings of the 9th Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages: Papers

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Self-Organizing Chinese and Japanese Semantic Maps
Qing Ma | Min Zhang | Masaki Murata | Ming Zhou | Hitoshi Isahara
COLING 2002: The 19th International Conference on Computational Linguistics

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Classification of Adjectival and Non-adjectival Nouns Based on their Semantic Behavior by Using a Self-Organizing Semantic Map
Kyoko Kanzaki | Qing Ma | Masaki Murata | Hitoshi Isahara
COLING-02: SEMANET: Building and Using Semantic Networks

2001

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Japanese Word Sense Disambiguation using the Simple Bayes and Support Vector Machine Methods
Masaki Murata | Masao Utiyama | Kiyotaka Uchimoto | Qing Ma | Hitoshi Isahara
Proceedings of SENSEVAL-2 Second International Workshop on Evaluating Word Sense Disambiguation Systems

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Using a Support-Vector Machine for Japanese-to-English Translation of Tense, Aspect, and Modality
Masaki Murata | Kiyotaka Uchimoto | Qing Ma | Hitoshi Isahara
Proceedings of the ACL 2001 Workshop on Data-Driven Methods in Machine Translation

2000

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Named Entity Extraction Based on A Maximum Entropy Model and Transformation Rules
Kiyotaka Uchimoto | Qing Ma | Masaki Murata | Hiromi Ozaku | Hitoshi Isahara
Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics

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Similarities and Differences among Semantic Behaviors of Japanese Adnominal Constituents
Kyoko Kanzaki | Qing Ma | Hitoshi Isahara
NAACL-ANLP 2000 Workshop: Syntactic and Semantic Complexity in Natural Language Processing Systems

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Hybrid Neuro and Rule-Based Part of Speech Taggers
Qing Ma | Masaki Murata | Kiyotaka Uchimoto | Hitoshi Isahara
COLING 2000 Volume 1: The 18th International Conference on Computational Linguistics

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Bunsetsu Identification Using Category-Exclusive Rules
Masaki Murata | Kiyotaka Uchimoto | Qing Ma | Hitoshi Isahara
COLING 2000 Volume 1: The 18th International Conference on Computational Linguistics

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Word Order Acquisition from Corpora
Kiyotaka Uchimoto | Masaki Murata | Qing Ma | Satoshi Sekine | Hitoshi Isahara
COLING 2000 Volume 2: The 18th International Conference on Computational Linguistics

1999

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An example-based approach to Japanese-to-English translation of tense, aspect, and modality
Masaki Murata | Qing Ma | Kiyotaka Uchimoto | Hitoshi Isahara
Proceedings of the 8th Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages

1998

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A Multi-Neuro Tagger Using Variable Lengths of Contexts
Susann LuperFoy | Dan Loehr | David Duff | Keith Miller | Florence Reeder | Lisa Harper | Qing Ma | Hitoshi Isahara
36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, Volume 2

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A Multi-Neuro Tagger Using Variable Lengths of Contexts
Qing Ma | Hitoshi Isahara
COLING 1998 Volume 2: The 17th International Conference on Computational Linguistics