- ÏÀʸ¤ÎPDF¤Î¥ê¥ó¥¯À褬ÀÚ¤ì¤Æ¤¤¤ë¾ì¹ç¤Ï¡¤ËܳؤÎÅŻҿ޽ñ´Û¤Î³Ø°ÌÏÀʸ¤Î¥Ú¡¼¥¸ http://library.naist.jp/library/thesis/index-j.html ¤«¤é³ºÅöÏÀʸ¤òõ¤·¤Æ²¼¤µ¤¤¡¥
Çî»ÎÏÀʸ†
2019ǯ 12·î ½¤Î»†
- Construction and Analysis of Multiword Expression-Aware Dependency Corpus
- ²ÃÆ£ ÌÀɧ
- [ PDF ]
2019ǯ 9·î ½¤Î»†
- Relation Extraction: Perspective from Weakly Supervised Methods
- Phi Van Thuy
- [ PDF ]
2019ǯ 6·î ½¤Î»†
- Computer-assisted Japanese Functional Expression Learning for Chinese-speaking Learners
- Liu Jun
- [ PDF ]
2019 (Ê¿À®31) ǯ 3·î ½¤Î»†
- Perspectives on the Making of Multiple Emotion Detection System in Text
- Phan Duc Anh
- NAIST-IS-DD1461213[ PDF ]
- Context Enhancement of Recurrent Neural Network Language Models for Automatic Speech Recognition
- Michael Alexander Hentschel
- [ PDF ]
2018 (Ê¿À®30) ǯ 3·î ½¤Î»†
- Studies on improving two fundamental steps for Chinese natural language processing: word segmentation and spelling check
- Äø Èô
- NAIST-IS-DD1361023 [ PDF ]
- An Exemplar-Based Approach to Word Representation for Information Extraction
- ßÀ¸ý ÂóÃË
- NAIST-IS-DD1461008 [ PDF ]
- A Study on Syntactic and Semantic Dependency Parsing
- ÂçÆâ ·¼¼ù
- NAIST-IS-DD1561004 [ PDF ]
- Neural Substrates of Individual Difference from Whole-brain Functional Connectivity
- ¹âÌÚ Í¥
- NAIST-IS-DD1561014 [ PDF ]
2017 (Ê¿À®29) ǯ 6·î ½¤Î»†
- Generating and Exploiting Language Resources for Indonesian Preposition Error Correction
- Budi Irmawati
- NAIST-IS-DD1261204 [ PDF ]
- Hierarchical Word Sequences Structures for Language Modeling
- ¸â ¶Ç°ì
- NAIST-IS-DD1361024 [ PDF ]
2017 (Ê¿À®29) ǯ 3·î ½¤Î»†
- Improving Nearest Neighbor Methods from the Perspective of Hubness Phenomenon
- ½ÅƣͥÂÀϺ
- NAIST-IS-DD1461004 [ PDF ]
- Recurrent Neural Networks for Natural Language and Biological Sequence
- ÄØ¿¿»Ë
- NAIST-IS-DD1461006 [ PDF ]
- Improving Formal Document Translation Using Sublanguage-Specific Sentence Structure
- Éٻν¨
- NAIST-IS-DD1561018 [ PDF ]
- Perspectives on the Marking of Discourse Relations: Cognitive Models and Machine Translation
- YUNG PIKYU FRANCES
- NAIST-IS-DD1461023 [ PDF ]
2016 (Ê¿À®28) ǯ 3·î ½¤Î»†
- Collocation Writing Assistant for Learners of Japanese as a Second Language
- Lis Weiji Kanashiro Pereira
- NAIST-IS-DD1361016 [ PDF ]
- Automatic Error Tag Annotation on the Writing of Japanese Language Learners for Linguistic and Educational Research
- Â绳¹ÀÈþ
- NAIST-IS-DD0661003 [ PDF ]
2015 (Ê¿À®27) ǯ 9·î ½¤Î»†
- Latent Variable Models for Bag-of-Words Data Based on Kernel Embeddings of Distributions
- µÈÀîͧÌé
- NAIST-IS-DD1361013 [ PDF ]
2015 (Ê¿À®27) ǯ 6·î ½¤Î»†
- Automated Grammatical Error Correction Using Statistical Machine Translation Techniques with Revision Log of Language Learning SNS
- ¿åËÜ ÃÒÌé
- NAIST-IS-DD1261016[ PDF ]
2015 (Ê¿À®27) ǯ 3·î ½¤Î»†
- Åý·×Ūµ¡³£³Ø½¬¤òÍѤ¤¤¿ÆüËܸìÎò»Ë¥³¡¼¥Ñ¥¹¹½ÃÛ»þ¤ÎɽµÀ°Íýºî¶È¤Î¼«Æ°²½
- ²¬ ¾È¹¸
- NAIST-IS-DD1261003[ PDF ]
- Bilingual Dictionary Extraction via Multilingual Topic Models
- Xiaodong Liu
- NAIST-IS-DD1161205 [ PDF ]
2014 (Ê¿À®26) ǯ 3·î ½¤Î»†
- ÆüËܸìÄÌ»þ¥³¡¼¥Ñ¥¹¤Î¤¿¤á¤Î·ÁÂÖÏÀ¾ðÊ󥢥Υơ¼¥·¥ç¥ó¤Î¸¦µæ
- ¾®ÌÚÁ¾ ÃÒ¿®
- NAIST-IS-DD1161018 [ PDF ]
- Japanese Predicate Argument Structure Analysis Based on Positional Relations between Predicates and Arguments
- ÎÓÉô Í´ÂÀ
- NAIST-IS-DD1161009 [ PDF ]
2013 (Ê¿À®25) ǯ 9·î ½¤Î»†
- Syntactic Dependency Structure-based Approaches for Chinese Semantic Role Labeling
- Íå ɧɧ
- NAIST-IS-DD1061033 [ PDF ]
- Automatic Summarization on Various Domains with Combinatorial Optimization and Machine Learning
- À¾Àî ¿Î
- NAIST-IS-DD1261010 [ PDF ]
- Statistical Induction of Tree-Generating Grammars for Natural Language Parsing
- ¿ÊÆ£ ͵Ƿ
- NAIST-IS-DD1261202[ PDF ]
2013 (Ê¿À®25) ǯ 3·î ½¤Î»†
- A Study of Algebraic and Graph-Theoretic Frameworks for Generalized Forward-Backward
Algorithms
- Åì Íõ
- NAIST-IS-DD0561001 [ PDF ]
- Techniques for Improving Transition-based Dependency Parsing Algorithms
- ÎÓ ¹îɧ
- NAIST-IS-DD1061018 [ PDF ]
2012 (Ê¿À®24) ǯ 9·î ½¤Î»†
- Extracting Named Entity Relations from Large Text Corpora
- Ê¿Ìî Å°
- NAIST-IS-DD1061203 [ PDF ]
- Design and Development of Optimized Hygienic Input Systems for Touch Screen Gadgets
- Asad Habib
- NAIST-IS-DD0961209 [ PDF ]
2012 (Ê¿À®24) ǯ 3·î ½¤Î»†
- Statistical and graph-based approaches to small sample and high dimensional data
- ÎëÌÚ °êÈþ
- NAIST-IS-DD0661014 [ PDF ]
- Development of Pairwise Comparison-based Japanese Dependency Parsers and Application to Corpus Annotation
- ´äΩ ¾ÏÂ
- NAIST-IS-DD0961004 [ PDF ]
- Organizing Information Based on Semantic Relation Recognition
- ¿åÌî ½ßÂÀ
- NAIST-IS-DD0961023 [ PDF ]
2011 (Ê¿À®23) ǯ 9·î ½¤Î»†
- Probabilistic Logic Approach to Event Structure Analysis (³ÎΨŪÏÀÍý¤Ë¤è¤ë»ö¾Ý¹½Â¤²òÀÏ)
- µÈÀî ¹îÀµ
- NAIST-IS-DD0961024 [ PDF ]
2011 (Ê¿À®23) ǯ 3·î ½¤Î»†
- Chinese Synthetic Word Analysis using Large-scale N-grams and An Extendable Lexicon Management System (Â絬ÌϤÊN-grams¥Ç¡¼¥¿¤òÍѤ¤¤¿Ãæ¹ñ¸ì¹çÀ®¸ì²òÀϵڤӳÈÄ¥¤Ç¤¤ë¸ì×ôÉÍý¥·¥¹¥Æ¥à)
- Ϥ ²Å
- NAIST-IS-DD0861027 [ PDF ]
2010 (Ê¿À®22) ǯ 12·î ½¤Î»†
- An Educational Technological Study on Computational Supports for Learning Linguistic Styles
(¸À¸ì¥¹¥¿¥¤¥ë½¬ÆÀ¤Î·×»»µ¡»Ù±ç¤Ë´Ø¤¹¤ë¶µ°é¹©³Ø¸¦µæ)
- ¶¶ËÜ ´îÂåÂÀ
- NAIST-IS-DD9861017 [ PDF ]
2010 (Ê¿À®22) ǯ 9·î ½¤Î»†
- °åÎÅʸ½ñ¤Î¼«Æ°ÅÀ»úËÝÌõ¤Ë¤ª¤±¤ëÀºÅÙ¸þ¾åË¡
- ¿ûÌî °¡µª
- NAIST-IS-DD0161020 [ PDF ]
2010 (Ê¿À®22) ǯ 3·î ½¤Î»†
- Event Relation Acquisition from Large Text Corpora
(Â絬Ìϥƥ¥¹¥È¤«¤é¤Î»öÂÖ´Ö´Ø·¸Ãμ±¤Î³ÍÆÀ)
- °¤Éô ½¤Ìé
- NAIST-IS-DD0561002 [ PDF ]
- Applying Deep Grammars to Machine Translation, Paraphrasing, and
Ontology Construction
(µ¡³£ËÝÌõ¡¢¸À¤¤´¹¤¨¡¢¥ª¥ó¥È¥í¥¸¡¼¹½Ãۤؤο¼¤¤Ê¸Ë¡¤ÎŬÍÑ)
- Eric Nichols
- NAIST-IS-DD0561041 [ PDF ]
- ¸úΨŪ¤Ê¶á˵¸¡º÷¤Î¤¿¤á¤Î¥Ô¥Ü¥Ã¥È³Ø½¬Ë¡
- ÌÚ¼ ³Ø
- NAIST-IS-DD0761013 [ PDF ]
- Graph-Theoretic Approaches to Minimally-Supervised Natural Language
Learning (¥°¥é¥ÕÍýÏÀŪ´ÑÅÀ¤«¤é¤Î¼«Á³¸À¸ì½èÍý¤Ë¤ª¤±¤ë¼å¶µ»Õ¤¢¤ê³Ø½¬)
- ¾®Ä® ¼é
- NAIST-IS-DD0761015 [ PDF ]
- Dependency-based Predicate-Argument Structure Analysis Using
Structured Learning and Named Entity Information (°Í¸¹½Â¤¤È¸ÇÍɽ¸½¾ðÊó¤òÍѤ¤¤¿¹½Â¤³Ø½¬¤Ë¤è¤ë½Ò¸ì¹à¹½Â¤²òÀÏ)
- ÅÏîµ ÍÛÂÀϺ
- NAIST-IS-DD0761031 [ PDF ]
2009 (Ê¿À®21) ǯ 9·î ½¤Î»†
- An Analysis of Non-Task-Oriented Dialogs and a Computational Model of Generating Affective Utterances (»¨ÃÌÂÐÏäÎʬÀϤȴ¶¾ð±þÅúÀ¸À®)
- ÆÁµ× ÎÉ»Ò
- NAIST-IS-DD0761020 [ PDF ]
2009 (Ê¿À®21) ǯ 3·î ½¤Î»†
- Constructing, Refining and Exploiting Rich Linguistic Rescources
(¸À¸ì»ñ¸»¤Î¹½ÃÛ/ÀºÏ£/ÍøÍÑÊýË¡¤Î¸¦µæ)
- Æ£ÅÄ¡ÊÀî°æ¡ËÁáÉÄ
- NAIST-IS-DD0361008 [ PDF ]
- Domain Adaptation of Statistical Word Segmentation System
(Åý·×Ūñ¸ìʬ³ä¤ÎʬÌîŬ±þ¼êË¡)
- ÄÚ°æ Í´ÂÀ
- NAIST-IS-DD0561205 [ PDF ]
2008 (Ê¿À®20) ǯ 3·î ½¤Î»†
- Biomedical Text Mining Based on Machine Learning: from Information Extraction to Coordination Identification
(µ¡³£³Ø½¬¤òÍѤ¤¤¿¥Æ¥¥¹¥È¥Þ¥¤¥Ë¥ó¥° ¡½°åΞðÊóÃê½Ð¤«¤éÊÂÎó¶ç²òÀϤޤǡ½)
- ¸¶ °ìÉ×
- NAIST-IS-DD0461029 [ PDF ]
- Constrcting a Temporal Relation Identification System of Chinese based on Dependency Structure Analysis
(°Í¸¹½Â¤¤Ë´ð¤Å¤¯Ãæ¹ñ¸ì»ö¾Ýɽ¸½¤Î»þ´Ö´Ø·¸Æ±Äꥷ¥¹¥Æ¥à¤Î¹½Ãۤ˴ؤ¹¤ë¸¦µæ)
- Yuchang CHENG
- NAIST-IS-DD0561040 [ PDF ]
2007ǯ 3·î ½¤Î»†
- Identification of Multi-Sentence Question Type and Extraction of Descriptive Answer in Open Domain Question-Answering
(ʬÌî¤ò¸ÂÄꤷ¤Ê¤¤¼ÁÌä±þÅú¤Ë¤ª¤±¤ëÊ£¿ôʸ¼ÁÌä¤Î¼±Ê̤ȵ½ÒŪ¤Ê²óÅú¤ÎÃê½Ð)
- ÉðÃÒ Êö¼ù
- NAIST-IS-DD0061208 [ PDF ]
- Combining Linguistic Knowledge and Machine Learning for Anaphora Resolution
(¾È±þ²òÀϤΤ¿¤á¤Î¸À¸ì³ØŪÃμ±¤Èµ¡³£³Ø½¬¼êË¡¤ÎÍ»¹ç)
- ÈÓÅÄ Î¶
- NAIST-IS-DD0461004 [ PDF ]
- Link Analysis with Kernel Metrics
(¥«¡¼¥Í¥ëµ÷Î¥¤òÍѤ¤¤¿¥ê¥ó¥¯²òÀÏ)
- °ËÆ£ ·Éɧ
- NAIST-IS-DD0461005 [ PDF ]
- Opinion Mining from Web documents¡§ Extraction and Structurization
(Webʸ½ñ¤òÂоݤȤ·¤¿°Õ¸«¾ðÊó¤ÎÃê½Ð¤È¹½Â¤²½)
- ¾®ÎÓ ¤Î¤¾¤ß
- NAIST-IS-DD0461010 [ PDF ]
2006ǯ 9·î ½¤Î»†
- Unknown Word Identification for Chinese Morphological Analysis
(Ãæ¹ñ¸ì·ÁÂÖÁDzòÀϤΤ¿¤á¤Î̤ÃθìÃê½Ð)
- GOH, Chooi-Ling
- NAIST-IS-DD0361217 [ PDF ]
- Discriminative Learning Methods for Interdependent Decision Problems in Natural Language Processing(¼«Á³¸À¸ì½èÍý¤Ë¤ª¤±¤ëÁê¸ß°Í¸ͽ¬ÌäÂê¤ËÂФ¹¤ë¼±Ê̳ؽ¬Ë¡¤Î¸¦µæ)
- ²ìÂô½¨¿Í
- NAIST-IS-DD0461007 [ PDF ]
2006ǯ 3·î ½¤Î»†
- Multilingual Word Segmentation and Part-of-Speech Tagging: a Machine Learning Approach Incorporating Diverse Features
(¿¸À¸ì¤Îñ¸ìʬ³ä¤ÈÉʻ쥿¥°ÉÕ¤±¡§Â¿ÍͤÊÁÇÀ¤òÍøÍѤ·¤¿µ¡³£³Ø½¬¤Ë¤è¤ë¥¢¥×¥í¡¼¥Á)
- ÃæÀîů¼£
- NAIST-IS-DD461022 [ PDF ]
2005ǯ 3·î ½¤Î»†
- A Constraint-based Grammar Approach to Japanese Sentence Processing:
Designing a Systematic Parser for Fundamental Grammatical Constructions
and Its Extensions with Semantic and Pragmatic Constraints
(ÆüËܸìʸ½èÍý¤Ø¤ÎÀ©Ìó¤Ë¤â¤È¤Å¤¯Ê¸Ë¡¤Ë¤è¤ë¥¢¥×¥í¡¼¥Á:½ÅÍ×¹½Ê¸¤ËÂФ¹¤ëÂηÏŪ¤Ê¥Ñ¡¼¥µ¤ÎÀ߷פȰỌ̃Ū¡¦¸ìÍÑŪÀ©Ìó¤òÍѤ¤¤¿³ÈÄ¥)
- Âçëϯ
- NAIST-IS-DD9961008 [ PDF ]
- Distributional Approaches to Natural Language Processing
(¼«Á³¸À¸ì½èÍý¤Ø¤ÎʬÉÛŪ¥¢¥×¥í¡¼¥Á)
- »ý¶¶ÂçÃÏ
- NAIST-IS-DT0061024 [ PDF ]
- Computation of Semantic Equivalence for Question Answering¡×¡Ê¼ÁÌä±þÅú¤Î¤¿¤á¤Î°Ọ̃ŪÅù²ÁÀ¤Îɾ²Á¡Ë
- ¹â¶¶¡¡Å¯Ï¯
- NAIST-IS-DT0261015 [ PDF ]
- Automatic Generation of Syntactically Well-formed and Semantically Appropriate Paraphrases
(Åý¸ìŪ¡¦°Ọ̃Ū¤ËŬ³Ê¤Ê¸À¤¤´¹¤¨¤Î¼«Æ°À¸À®)
- Æ£ÅÄÆÆ
- NAIST-IS-DT0261023 [ PDF ]
- Kernels for Application Tasks in Natural Language Processing
(¹½Â¤¾ðÊó¤òÍøÍѤ·¤¿¥«¡¼¥Í¥ë¤Ë´ð¤Å¤¯¼«Á³¸À¸ì½èÍý)
- ÎëÌÚ½á
- NAIST-IS-DT0361207 [ PDF ]
2004ǯ 12·î ½¤Î»†
- Machine Learning in Rhetorical Parsing and Open-domain Text Summarization (½¤¼¹½Â¤²òÀϤȥƥ¥¹¥È¼«Æ°Í×Ì󡧵¡³£³Ø½¬¤Ë¤è¤ëÀܶá)
- ÌîËÜ Ãé»Ê
- NAIST-IS-DD9761210 [ PDF ]
- Translation Knowledge Acquisition for Pattern-based Machine Translation (¥Ñ¥¿¡¼¥ó¥Ù¡¼¥¹µ¡³£ËÝÌõ¤Î¤¿¤á¤ÎËÝÌõÃμ±³ÍÆÀ)
- Ë̼ ÈþÊæ»Ò
- NAIST-IS-DD9961202 [ PDF ]
2004ǯ 9·î ½¤Î»†
- Acquiring Paraphrases from Corpora and Its Application to Machine Translation (¥³¡¼¥Ñ¥¹¤«¤é¤Î¥Ñ¥é¥Õ¥ì¡¼¥º¤Î³ÍÆÀ¤È¤½¤Îµ¡³£ËÝÌõ¤Ø¤ÎŬÍÑ)
- ²¼Èª ¸÷É×
- NAIST-IS-DT0261014 [ PDF ]
2004ǯ 6·î ½¤Î»†
- Automatic Construction of Translation Knowledge for Corpus-based Machine Translation (¥³¡¼¥Ñ¥¹¥Ù¡¼¥¹µ¡³£ËÝÌõ¤Ë¤ª¤±¤ëËÝÌõÃμ±¼«Æ°¹½ÃÛË¡¤Î¸¦µæ)
- º£Â¼ ¸¼£
- NAIST-IS-DT0261006 [ PDF ]
2004ǯ 3·î ½¤Î»†
- Acquiring Causal Knowledge from Text Using Connective Markers (Àܳɸ¼±¤Ë´ð¤Å¤¯Ê¸½ñ½¸¹ç¤«¤é¤Î°ø²Ì´Ø·¸Ãμ±³ÍÆÀ)
- ´¥ ¹§»Ê
- NAIST-IS-DT0161005 [ PDF ]
- Machine Learning and Data Mining Approaches to Practical Natural Language Processing (µ¡³£³Ø½¬¤È¥Ç¡¼¥¿¥Þ¥¤¥Ë¥ó¥°¤òÍѤ¤¤¿¸½¼ÂŪ¤Ê¼«Á³¸À¸ì½èÍý)
- ¹©Æ£ Âó
- NAIST-IS-DT0161013 [ PDF ]
- Synthetic Assistance for Creation and Communication of Information (¸¡º÷µ»½Ñ¤È¥³¥ß¥å¥Ë¥±¡¼¥·¥ç¥óµ»½Ñ¤Ë´Ø¤¹¤ë¸¦µæ)
- ¹âÎÓ Å¯
- NAIST-IS-DT0161025 [ PDF
2003ǯ 12·î ½¤Î»†
- Corpus-based Japanese morphological analysis
- Àõ¸¶ Àµ¹¬
- NAIST-IS-DT0161001 [ PDF ]
2003ǯ 3·î ½¤Î»†
- Clustering Approaches to Text Categorization (ʸ½ñʬÎà¤Ø¤Î¥¯¥é¥¹¥¿¥ê¥ó¥°¤Ë¤è¤ë¥¢¥×¥í¡¼¥Á)
- ¹â¼ ÂçÌé
- NAIST-IS-DT0061014 [ PDF ]
2002ǯ 9·î ½¤Î»†
- A Study on Generic and User-Focused Automatic Summarization (°ìÈÌŪ¤ÊÍ×Ìó¤È»ëÅÀ¤ò¹Íθ¤·¤¿Í×Ìó¤Ë´Ø¤¹¤ë¸¦µæ)
- Ê¿Èø ÅØ
- NAIST-IS-DT0061021 [ PDF ]
2002ǯ 3·î ½¤Î»†
- Text Categorization Using Machine Learning (µ¡³£³Ø½¬¤òÍѤ¤¤¿¥Æ¥¥¹¥ÈʬÎà)
- Ê¿ Çî½ç
- NAIST-IS-DT0061207 [ PDF ]
- A Study on Operations Used in Text Summarization (¥Æ¥¥¹¥È²òÀϤ˴ð¤Å¤¯¼«Æ°Í×Ìó¤Î´ðÁø¦µæ)
- ÃÝÆâ Ϲ
- NAIST-IS-DT9961016 [ PDF ]
- Â絬ÌϸÀ¸ì¥³¡¼¥Ñ¥¹¤Î²òÀϤȸ¡º÷¤Ë´Ø¤¹¤ë¸¦µæ
- »³²¼Ã£Íº
- NAIST-IS-DT9761025 [ PDF ]
- Partial Language Analysis Using Support Vector Learning (Support Vector ³Ø½¬¤òÍѤ¤¤¿Éôʬ¸À¸ì²òÀÏ)
- »³ÅÄ ´²¹¯
- NAIST-IS-DT9961028 [ PDF ]
- Extracting Translation Knowledge from Parallel Corpora (¥³¡¼¥Ñ¥¹¤«¤é¤ÎËÝÌõÃμ±Ãê½Ð)
- »³ËÜ ·°
- NAIST-IS-DT9961030 [ PDF ]
2001ǯ 9·î ½¤Î»†
- Cross-language Information Retrieval, Document Alignment and Visualization --- A Study with Japanese and Chinese (¿¸À¸ì´Ö¾ðÊ󸡺÷ --- ʸ½ñÂбþÉÕ¤±¤È¤½¤Î»ë³Ð²½)
- Md. Maruf Hasan
- NAIST-IS-DT9861207 [ PDF ]
2000ǯ 3·î ½¤Î»†
- Japanese Dependency Structure Analysis Based on a Lexicalized Statistic Model (¸ì×ÃÅý·×¥â¥Ç¥ë¤Ë´ð¤Å¤¤¤¿ÆüËܸ췸¤ê¼õ¤±²òÀÏ)
- Æ£Èø ÀµÏÂ
- NAIST-IS-DT9761017 [ PS ]
1998ǯ 9·î ½¤Î»†
- A Corpus-Based Study on Conversational Interaction in Japanese: Discourse Structures, Turn-Taking, and Backchannels (¥³¡¼¥Ñ¥¹¤Ë¤â¤È¤Å¤¯ÆüËܸì²ñÏÃ¥¤¥ó¥¿¥é¥¯¥·¥ç¥ó¤Î¸¦µæ: ÃÌÏù½Â¤, ÏüԸòÂØ, ¤¢¤¤¤Å¤Á)
- ¾®°ë ²Ö³¨
- NAIST-IS-DT9661010 [ PDF ]
- Çî»Î (Íý³Ø)
- A Machine Learning Approach to Natural Language Processing (¼«Á³¸À¸ì½èÍý¤Ø¤Îµ¡³£³Ø½¬¤Ë¤è¤ë¥¢¥×¥í¡¼¥Á)
- ½ÕÌî ²íɧ
- NAIST-IS-DT9761211 [ PDF ]
1998ǯ 3·î ½¤Î»†
- An Integrated Robust Parsing using Multiple Knowledge Sources (Ê£¿ô¤ÎÃμ±¸»¤òÅý¹çŪ¤ËÍѤ¤¤¿´è·ò¤Ê¼«Á³¸À¸ì½èÍý)
- º£°ì ½¤
- NAIST-IS-DT9561005
- Semantic Structures of Japanese Verb Phrases --- Acquisition, Representation and Use (ÆüËܸìÆ°»ì¶ç¤Î°ÕÌ£¹½Â¤ --- ³ÍÆÀ¡¤É½¸½¡¤ÍøÍÑ ---)
- ÂçÀÐ µü
- NAIST-IS-DT9561009 [ PS ]
- Building Morphology-Based Statistical Models for Japanese Language (Åý·×Ū·ÁÂÖÁDzòÀϤòÍѤ¤¤¿¸À¸ì¥â¥Ç¥ë)
- ÃÝÆâ ¹¦°ì
- NAIST-IS-DT9561208
- Supervised Learning of Syntactic Structure (¹½Ê¸¹½Â¤¤Î¶µ»ÕÉÕ¤³Ø½¬)
- Wide R. Hogenhout
- NAIST-IS-DT9561211
- Çî»Î (Íý³Ø)
½¤»ÎÏÀʸ¡¦²ÝÂ긦µæÊó¹ð½ñ†
2019ǯ 9·î ½¤Î»†
- Improving Knowledge Graph Completion Models by Unsupervised Type Constraint Inference
- Lu Yuxun
- Relation Classification Using Segment-Level Attention-based CNN and Dependency-based RNN
- Van_Hien Tran
2019ǯ 3·î ½¤Î»†
- Joint Prediction of Morphosyntactic Categories for Fine-Grained Arabic Part-of-Speech Tagging Exploiting Tag Dictionary Information
- °æ¾å ¹ä
- Semantic Machine Translation Evaluation without References
- Michael Wentao Li
- Neural Tensor Networks with Diagonal Slice Matrices
- Àи¶ ·ÉÂç
- µ¡³£Æɲò¤Ë¤ª¤±¤ë Answer Sentence Selection ¤ÎºÆ¹Í
- º´¡¹ÌÚ ½Ó¼ù
- ÍÑÎãÃæ¤Îñ¸ì¤ò½Å¤ßÉÕ¤±Ï¤ˤè¤êÍøÍѤ·¤¿ÆüËܸì½Ò¸ì¹à¹½Â¤²òÀÏ
- ¼Ç¸¶ δÁ±
- Stochastic Tokenization with Language Model for Neural Text Classification
- Ê¿²¬ ãÌé]
- Ãí°Õµ¡¹½¤Ë¤è¤ë²èÁüÆÃħÎÌÁªÂò¤òÍѤ¤¤¿²èÁüÉÕ¤´Þ°Õ´Ø·¸Ç§¼±
- ËÜ¿ ±¦µþ
- An Empirical Study on Reduction of Parameter Redundancy in a Weight Matrix in a Biaffine Parser
- ¾¾Ìî ÃÒµª
- Unsupervised Multilingual Word Embedding with Limited Resources using Neural Language Models
- ÏÂÅÄ ¿ò»Ë
- °å³ØÀ¸Êª³ØÏÀʸ¤«¤é¤Î¾ðÊóÃê½Ð
- ÅÏî´ ¸Ìé
- ¿ÍͤʥΥ¤¥º¤Ë´è·ò¤Ê´Ø·¸¥Ç¡¼¥¿¥¯¥é¥¹¥¿¥ê¥ó¥°
- ÉðÅÄ ÍªÍ¤
2018ǯ 3·î ½¤Î»†
- ¿¼Áسؽ¬¤Ë¤è¤ëÇжç¤Î¼«Æ°À¸À®
- ÂÀÅÄàö»Ò
- NAIST-IS-MT1651023
- ¥¯¥é¥¹¥¿¥ê¥ó¥°¤òÍøÍѤ·¤¿¿¼Áسؽ¬¤Ë¤è¤ëÆüËܸìÊ£¹ç¼¤Î¸¡½Ð
- µ×ÊÝÂçµ±
- NAIST-IS-MT1651046
- ¥Á¥ã¥ó¥¯¤Ë´ð¤Å¤¤¤¿Ã༡·¿Åý¹ç¥Ñ¡¼¥¸¥ó¥°
- ¾®ÈæÅÄÎòð
- NAIST-IS-MT1651047
- Cross-Domain and Cross-Lingual Parsing with Adversarial Training (ŨÂгؽ¬¤òÍѤ¤¤¿Ê¬Ìî¤È¸À¸ì¤ò²£ÃǤ¹¤ë¹½Ê¸²òÀÏ)
- º´Æ£¸µµª
- NAIST-IS-MT1651053
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- Liu Xinran
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- Alivanh Insisiengmay
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2016ǯ 9·î ½¤Î»†
- Integrating Word Embedding Offsets into the Espresso System for Part-Whole Relation Extraction
- Phi Van Thuy
- NAIST-IS-MT1451208
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- Semantic Structure Analysis of Noun Phrases using Abstract Meaning Representation
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- Mixture of Topic Models for Analyzing Short Text Documents with User Information
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2015ǯ 9·î ½¤Î»†
- Extracting Bilingual Multi-word Terms from Comparable Corpora
- Liang Jun
- NAIST-IS-MT1351208
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- Transition-based Dependency Parsing Exploiting Supertags (Supertag¤òÍøÍѤ·¤¿Á«°Ü·¿°Í¸¹½Â¤²òÀÏ)
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- Visualizing Words and Documents for Revealing Multisense Words
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- Factored Translation Models¤òÍѤ¤¤¿»ö¸åʤÙÂؤ¨¤Ë¤è¤ëÆü±ÑËÝÌõ
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- Modeling of Semantic Co-Compositionality and Learning of Word Representations
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- NAIST-IS-MT1251081
- Synergies between Word Representations Learning and Dependency Parsing
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- NAIST-IS-MT1251119
- ImprovingWord Alignment for Statistical Machine Translation by Prediction of Unalignable Words
- Frances Yung Pikyu
- NAIST-IS-MT1251126
- Efficient K-Nearest Neighbor Graph Construction Using MapReduce for Large-Scale Data Sets
- ÏÂÎÉÉÊ Í§Âç
- NAIST-IS-MT1251121
2013ǯ 3·î ½¤Î»†
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- NAIST-IS-MT0951036
- Collocation Suggestion for Japanese Second Language Learners¡ÊÆüËܸì³Ø½¬¼Ô¤Î¤¿¤á¤Î¥³¥í¥±¡¼¥·¥ç¥óÄ󼨡Ë
- Lis Kanashiro
- NAIST-IS-MT1151128
- Using Large-scale unlabeled data for parsing internal structure of Chinese Synthetic words¡ÊÃæ¹ñ¸ì¤Î¹çÀ®¸ì¤ÎÆâÉô¹½Â¤²òÀϤؤÎÂ絬Ìϥǡ¼¥¿ÍøÍÑ¡Ë
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- A Monte Carlo Method for Hilbert Space Embeddings of Distributions and Its Application to Filtering in State Space Models¡Ê¥â¥ó¥Æ¥«¥ë¥íË¡¤Ë¤è¤ë³ÎΩʬÉۤΥҥë¥Ù¥ë¥È¶õ´ÖËä¹þ¤ß¤È¤½¤Î¾õÂÖ¶õ´Ö¥â¥Ç¥ë¤Î¥Õ¥£¥ë¥¿¥ê¥ó¥°¤Ø¤Î±þÍÑ¡Ë
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- Joint English Spelling Error Correction and POS tagging for Language Learning Writing¡Ê±Ñ¸ì¥¹¥Ú¥ê¥ó¥°ÄûÀµ¤ÈÉʻ쥿¥°ÉÕ¤±¤ÎƱ»þ²òÀÏ¡Ë
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- Information Diffusion Models for Capturing Latent Factors of Real World Phenomena on Social Networks¡Ê¥½¡¼¥·¥ã¥ë¥Í¥Ã¥È¥ï¡¼¥¯¤Ë¤ª¤±¤ë¸½¼ÂÀ¤³¦¤Î¸½¾Ý¤ÎÀøºß°ø»Ò¤òª¤¨¤ë¤¿¤á¤Î¾ðÊó³È»¶¥â¥Ç¥ë¡Ë
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- NAIST-IS-MT1151114
2012ǯ 9·î ½¤Î»†
- Analysis of Patterns of Complex Sentences for Statistical Translation
- To Thi Chinh
- NAIST-IS-MT1051206
2012ǯ 3·î ½¤Î»†
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- NAIST-IS-MT1051075
- Automated Japanese Error Correction with Revision Logs of Language Learning SNS
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- NAIST-IS-MT1051107
- Transfer Learning for Multiple-Domain Sentiment Analysis
- µÈÅÄ ¹¯µ×
- NAIST-IS-MT1051124
- Narrative Schema as World Knowledge for Coreference Resolution
- JOSEPH HOWARD IRWIN
- NAIST-IS-MT1051134
2011ǯ 3·î ½¤Î»†
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- NAIST-IS-MR0951002
- Short-text Oriented Chinese Named Entity Recognition (¥·¥ç¡¼¥È¥á¥Ã¥»¡¼¥¸Ãæ¤ÎÃæ¹ñ¸ì¸ÇÍɽ¸½Ãê½Ð)
- Jiawei Ye
- NAIST-IS-MT0951137
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- Mutual k-Nearest Neighbor Graphs for Semi-Supervised Learning
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- NAIST-IS-MT0951027
- Unsupervised Seed Selection and Stop List Construction for Bootstrapping: a Graph-based Approach (¥Ö¡¼¥È¥¹¥È¥é¥Ã¥Ô¥ó¥°¤Ë¤ª¤±¤ë¥°¥é¥Õ¤Ë´ð¤Å¤¯¥·¡¼¥ÉÁªÂò¤ª¤è¤Ó¥¹¥È¥Ã¥×¥ê¥¹¥È¹½ÃÛ)
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2010ǯ 3·î ½¤Î»†
- Handling Tokenization Ambiguities in English Part-of-Speech Tagging
- Alex Shinn
- NAIST-IS-MT0751204
- Æ°»ì¤Î¹à¹½Â¤¼½ñ¤òÍøÍѤ·¤¿»öÂÖÀ̾»ì¤Î¹àƱÄê
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- NAIST-IS-MT0851003
- Anaphora Resolution for Japanese Definite Noun Phrases¡ÊÆüËܸì¤ÎľÀܾȱþ¤ª¤è¤Ó´ÖÀܾȱþ¤ÎÅý¹çŪ²òÀÏ¡Ë
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- Evaluating Lexical/Semantic Resources for Bridging the Semantic Gap in Textual Inference
- Francisco Soares
- NAIST-IS-MT0851138
2009ǯ 3·î ½¤Î»†
- Japanese Dependency Parsing Using a Tournament Model
(¥È¡¼¥Ê¥á¥ó¥È¥â¥Ç¥ë¤òÍѤ¤¤¿ÆüËܸ췸¤ê¼õ¤±²òÀÏ)
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- NAIST-IS-MT0651102
- Cocytus: Parallel Natural Language Prossing over Disparate Data
- Noah Evans
- NAIST-IS-MT0651147
- Automatic Text Summarization with Probabilistic Latent Indexing
- Bhandari Harendra
- NAIST-IS-MT0651150
- Chinese Synthetic Words Analysis
- Ϥ ²Å
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- NAIST-IS-MT0551014
- Argument Structure Analysis of Event Nouns Based on Noun-verb Co-occurrences and Noun Phrase Patterns
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- NAIST-IS-MT0551054
- Webʸ½ñ¤òÍøÍѤ·¤¿È¾¶µ»Õ¤¢¤êÍѸìÃê½Ð
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- Ê¡²¬ Í´°ì
- NAIST-IS-MR0451105
- DOM¹½Â¤¤òÍøÍѤ·¤¿¾ò·ïÉÕ³ÎΨ¾ì¤Ë¤è¤ëWikipediaʸ½ñÃæ¤Î¸ÇÍɽ¸½¤Î°ÕÌ£ÂηϤؤγä¤êÅö¤Æ
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- NAIST-IS-MT0551137
- Learning from Data of Varying Quality for Sentence Role Identification in MEDLINE
- Natalia Aizenberg
- NAIST-IS-MT0551138
- Japanese-Spanish Thesaurus Construction Using English as a Pivot
- Jessica Ramirez
- NAIST-IS-MT0551142
2006ǯ 3·î ½¤Î»†
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- NAIST-IS-MR0451042
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- NAIST-IS-MT0451101
- Semi-Markov Conditional Random Fields¤òÍѤ¤¤¿¸ÇÍɽ¸½Ãê½Ð¤Ë´Ø¤¹¤ë¸¦µæ
- Ê¡²¬·òÂÀ
- NAIST-IS-MT0451104
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- NAIST-IS-MR0451204
2005ǯ 3·î ½¤Î»†
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- NAIST-IS-MT0351003
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- NAIST-IS-MT0351080
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- NAIST-IS-MT0351141
- Automatic extraction of fixed multiword expressions¡Ê±Ñ¸ì¤Ë¤ª¤±¤ë¸ÇÄêĹʣ¹ç¸ìɽ¸½¤Î¼«Æ°³ÍÆÀ¡Ë
- Campbell Hore
- NAIST-IS-MT0351147
- Chinese Deterministic Dependency Analyzer: Examining Effects of Chunking, Root node finder and Global Features¡Ê·èÄêÀ¤ÎÃæ¹ñ¸ì°Í¸¹½Â¤²òÀϴ¥Á¥ã¥ó¥«¡¼¡¢¥ë¡¼¥È¥Î¡¼¥È²òÀÏ´ïµÚ¤ÓÂç¶ÉÁÇÀ¤ÎƳÆþ¤Ë¤Ä¤¤¤Æ¸¦µæ¡Ë
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- NAIST-IS-MT0351204
- The Role of Dependency Trees in HPSG Parse Filtering¡ÊHPSG¹½Ê¸²òÀÏ¥Õ¥£¥ë¥¿¥ê¥ó¥°¤ÇÍѤ¤¤ë°Í¸¹½Â¤¡Ë
- Eric Nichols
- NAIST-IS-MT0351205
2004ǯ 3·î ½¤Î»†
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- MEDLINEʸ½ñ¸¡º÷¤Î¤¿¤á¤Îʸ¤ÎÌò³äʬÎà
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- NAIST-IS-MT0251126
- Application of Kernels to Citation Analysis¡Ê¥«¡¼¥Í¥ëË¡¤Ë´ð¤Å¤¯°úÍѲòÀÏ¡Ë
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- NAIST-IS-MT0251016
- Ï¢Àܸ½¾Ý¤ò²ð¤·¤¿HPSG¤Ë´ð¤Å¤¯½õ»ì¤ÎʬÀÏ
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- NAIST-IS-MT0251057
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- NAIST-IS-MT0251041
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- NAIST-IS-MT0251129
2003ǯ 9·î ½¤Î»†
- Chinese Unknown Word Identification by Combining Statistical Models (Ãæ¹ñ¸ì¤Î̤Ãθìǧ¼±¤Ë¤ª¤±¤ëÅý·×Ū¤Ê¼êË¡¤ÎÍøÍÑ)
- GOH Chooi Ling
- NAIST-IS-MT0151207
2003ǯ 3·î ½¤Î»†
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- NAIST-IS-MT0151048
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- NAIST-IS-MT0151115
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- ÊÆÅÄδ°ì
- NAIST-IS-MT0151124
- Data Classification and Question Generation in OSARU "A web based Japanese language acquisition support system"
- NEUPANE Bhooshan Raj
- NAIST-IS-MT0151129
2002ǯ 9·î ½¤Î»†
- Ãæ¹ñ¸ì¤ÈÆüËܸìÂÐÌõ¥³¡¼¥Ñ¥¹¤Î¤¿¤á¤Î¼«Æ°Ê¸¥¢¥é¥¤¥ó¥á¥ó¥È¤Î¸¦µæ
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- NAIST-IS-MT0051205
2002ǯ 3·î ½¤Î»†
- ʸ´Ö¤ÎÀܳ´Ø·¸¤òÍѤ¤¤¿¥Æ¥¥¹¥Èʬ³ä
- ÂçÅç Ë㵪»Ò
- NAIST-IS-MT0051014
- Authorship Identification for Heterogeneous Documents (°Û¤Ê¤ë¥¿¥¤¥×¤Î¥É¥¥å¥á¥ó¥È¤ËÂФ¹¤ëÃø¼Ô¿äÄê)
- ÄÚ°æ Í´ÂÀ
- NAIST-IS-MT0051063
- Morphological Analysis and Corpus Error Detection Using Support Vector Machines (Support Vector Machine ¤òÍѤ¤¤¿·ÁÂÖÁDzòÀϤȥ³¡¼¥Ñ¥¹¤Î¸í¤ê¸¡½Ð)
- ÃæÀî ů¼£
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- À¸À®¸ì×ÃÏÀ¤òÍѤ¤¤¿¥ò³Ê¤È¥µÊÑ̾»ì¤Îñ°ì²½¤Ë¤Ä¤¤¤Æ
- Ê¡ÅÄ ¾¡¿Î
- NAIST-IS-MT0051090
- OSARU, a Web-Based Japanese Language Acquisition Support System (¤ª¤µ¤ë¥¦¥§¥Ö¥Ù¡¼¥¹ÆüËܸì³Ø½¬»Ù±ç¥·¥¹¥Æ¥à)
- ¿¹Àî Áï
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- Ongart Supackchookul
- NAIST-IS-MT0051124
2001ǯ 3·î ½¤Î»†
- Extended Statistical Model for Morphological Analysis (ÆüËܸì·ÁÂÖÁDzòÀϤ«¤é¿¹ñ¸ì·ÁÂÖÁDzòÀϤØ)
- Àõ¸¶ Àµ¹¬
- NAIST-IS-MT9851001
- ²»À¼ÂÐÏäˤª¤±¤ë°Õ¿Þ¤äÏÃÂê°Ü¹Ô¤Îɽ½Ð¤Ë´Ø¤ï¤ë¸À¸ìÆÃħ¤ÎʬÀÏ
- ¾®Ìº ÆØ»Ò
- NAIST-IS-MT9951025
- Japanese Dependency Structure Analysis Based on Support Vector Machines (Support Vector Machine ¤òÍѤ¤¤¿ÆüËܸ췸¤ê¼õ¤±²òÀÏ)
- ¹©Æ£ Âó
- NAIST-IS-MT9951036
- Writing Assistance through Search Techniques (¸¡º÷µ»½Ñ¤òÍѤ¤¤¿ºîʸ»Ù±ç)
- ¹âÎÓ Å¯
- NAIST-IS-MT9951064
- ¼ÁÌä±þÅú¥·¥¹¥Æ¥à¤Ë¤ª¤±¤ëÃÊÍîÃê½Ð¤ÎÊýË¡¤Ë´Ø¤¹¤ë¸¦µæ
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- NAIST-IS-MT9951101
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- NAIST-IS-MT9951124
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- NAIST-IS-MT9951128
2000ǯ 3·î ½¤Î»†
- ´ØÏ¢ÀÍýÏÀ¤òÍѤ¤¤¿ÆüËܸ쥼¥íÂå̾»ì¤Î¾È±þ´Ø·¸¤ÎƱÄê
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- NAIST-IS-MT9851030
- °å³ØÀ¸Êª³Øʸ¸¥¤«¤é¤ÎÀìÌçÍѸì¤ÎÃê½Ð¤ÈʬÎà
- ¹ç¸¶ Çî
- NAIST-IS-MT9851036
- À¸À®¸ì×ä˴ð¤Å¤¯Ã±°ì²½¥¨¥ó¥¸¥ó¤òÍѤ¤¤¿ÆüËܸìÆ°»ì¶ç¤Î°ÕÌ£²òÀÏ
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- NAIST-IS-MT9851057
- Éʻ쥿¥°ÉÕ¤¥³¡¼¥Ñ¥¹ºîÀ®»Ù±ç´Ä¶¤Î¹½ÃÛ
- ¾¾ÅÄ ´²
- NAIST-IS-MT9851103
- Semantic Model and Semantic Analysis with a Stochastic Association (³ÎΨŪϢÁۤ˴ð¤Å¤¯°ÕÌ£¥â¥Ç¥ë¤È°ÕÌ£²òÀÏ)
- »ý¶¶ ÂçÃÏ
- NAIST-IS-MT9851113
1999ǯ 3·î ½¤Î»†
- ¥Ù¥¯¥È¥ë¶õ´Ö¥â¥Ç¥ë¤òÍѤ¤¤¿ÏÀʸ¸¡º÷¤Ë¤ª¤±¤ë¥Ù¥¯¥È¥ë²½Ë¡¤ª¤è¤Ó¤½¤Îɾ²Á
- ²¬ß· ¿Î
- NAIST-IS-MT9751022
- ʪ¸ìʸÃæ¤Î»þ´Öɽ¸½¤ÎʬÀϤȤ½¤ì¤òÍѤ¤¤¿Ê¸¾Ï¤Î¹½Â¤²½
- Æ£ÅÄ ÁáÉÄ
- NAIST-IS-MT9751092
- ¥Æ¥¥¹¥È½¤¼¹½Â¤¥¿¥°ÉÕ¤±¤ÎȾ¼«Æ°²½¤Ë´Ø¤¹¤ë¸¦µæ
- ÃÝÆâ Ϲ
- NAIST-IS-MT9751065
- ʸ¾ÏÃæ¤Î̾»ì´Ö¾È±þ´Ø·¸¤ÎƱÄê
- »³º¬ ÍÎÊ¿
- NAIST-IS-MT9751111
1998ǯ 3·î ½¤Î»†
- ¥³¡¼¥Ñ¥¹¤«¤é¤ÎÆüËܸ콾°Àá·¸¤ê¼õ¤±Áª¹¥¾ðÊó¤ÎÃê½Ð
- À¾²¬»³ ¼¢Ç·
- NAIST-IS-MT9551082
- ÆüËܸìʸ¤Î·¸¼õ¤±¹½Â¤¤òÍøÍѤ·¤¿¾ðÊ󸡺÷
- º£Â¼ ͧÌÀ
- NAIST-IS-MT9651011
- Acquisition of Nominal Lexical Knowledge from Japanese Corpora
- ²ÏÉô ¹±
- NAIST-IS-MT9651036
- ¸í¤ê¶îÆ°·¿¤Î³ÎΨ¥â¥Ç¥ë³Ø½¬¤Ë¤è¤ëÆüËܸì·ÁÂÖÁDzòÀÏ
- ËÌÆâ ·¼
- NAIST-IS-MT9651040
- ¶É½êÁêƱÀ¤òÍøÍѤ·¤¿ORF¤ÎʬÎॢ¥ë¥´¥ê¥º¥à³«È¯µÚ¤ÓÂçIJ¶Ý¥²¥Î¥à¤Ë¤ª¤±¤ë±þÍÑ
- ¥·¥Ð¥¹¥ó¥¿¥é¥ó ¥¹¥Ï¥ë¥Ê¥ó
- NAIST-IS-MT9651129
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- NAIST-IS-MT9651078
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- Ìî¸ý ¹¾´
- NAIST-IS-MT9651203
- ȯÏÃÀø»þ¬Äê¤òÍѤ¤¤¿Ä´²»±¿Æ°´ë²èÀ¸À®µ¡¹½¤Î¸¦µæ
- Æ£¸¶ ¾´É§
- NAIST-IS-MT9651094
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- NAIST-IS-MT9651124
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- NAIST-IS-MT9651125
1997ǯ 3·î ½¤Î»†
- ÉÊ»ì¾ðÊóÉÕ¤DTD¤òÍѤ¤¤¿³Ø½ÑÏÀʸ¥Æ¥¥¹¥È¤ÎSGML¥¿¥°ÉÕ¤±
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- NAIST-IS-MT9551009
- ¥³¡¼¥Ñ¥¹¤«¤é¤Î¶¦µ¯¾ðÊó¤òÍѤ¤¤¿¥·¥½¡¼¥é¥¹Æâ¤Î³µÇ°¹½Â¤¤ÎºÆ¹½ÃÛ
- Ê¿Èø ÅØ
- NAIST-IS-MT9551089
- ÍѸÀ¤Î³èÍѤò¹Íθ¤·¤¿´Ú¹ñ¸ìÉÊ»ìÂηϤÎÄó°Æ¤È¤½¤ì¤òÍѤ¤¤¿´Ú¹ñ¸ì·ÁÂÖÁDzòÀÏ
- Ê¿Ìî Á±Î´
- NAIST-IS-MT9551092
- Japanese Dependency Structure Analysis based on Lexicalized Statistic Model
- Æ£Èø ÀµÏÂ
- NAIST-IS-MT9551093
- ÅÅ»ÒÇÞÂÎʸ¾Ï¤«¤é´¶¾ð¤òÆɤߤȤëÊýË¡¤Ë´Ø¤¹¤ë¸¦µæ
- ´Ý»³ ¹¬»Ò
- NAIST-IS-MT9551106
- µ¬Â§¤È³ÎΨ¥â¥Ç¥ë¤ÎÅý¹ç¤Ë¤è¤ë·ÁÂÖÁDzòÀÏ
- »³²¼ ãͺ
- NAIST-IS-MT9551119
1996ǯ 9·î ½¤Î»†
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- À¾Åĸµ¼ù
- NAIST-IS-MT9451085
1996ǯ 6·î ½¤Î»†
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- ±©ÅÄ ¤æ¤«¤ê
- NAIST-IS-MR9551002
1996ǯ 3·î ½¤Î»†
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- NAIST-IS-MT9451002
- Bayes ¤Î·èÄêË¡¤òÍѤ¤¤¿Ê¸¾Ï¹½À®»Ù±ç
- ÃÓÅÄ Ê¸¿Í
- NAIST-IS-MT9451005
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- NAIST-IS-MR9451025
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- NAIST-IS-MT9451039
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- NAIST-IS-MT9451071
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- NAIST-IS-MT9451079
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- Ã滳 ÂóÌé
- NAIST-IS-MT9451083
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- NAIST-IS-MR9451116
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- NAIST-IS-MT9451122
1995ǯ 9·î ½¤Î»†
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- ÃÝÆâ ¹¦°ì
- NAIST-IS-MT9451067
- Enrichment of Models for Stochastic Grammars: Semantical Categories
- Wide Roeland Hogenhout
- NAIST-IS-MT9451207
1995ǯ 6·î ½¤Î»†
- ÏÀʸÁ´Ê¸¥Ç¡¼¥¿¥Ù¡¼¥¹¤Î¤¿¤á¤ÎSGML¥¿¥°ÉÕ¤±¤Î¼«Æ°²½
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1995ǯ 3·î ½¤Î»†
- An Ingetrated Framework for Processing Grammatically Ill-Formed Sentences
- Osamu IMAICHI
- NAIST-IS-MT351012
- ÂÐÌõ¥³¡¼¥Ñ¥¹¤«¤é¤ÎËÝÌõÃμ±¤Î³ÍÆÀ¤Èµ¡³£ËÝÌõ¤Ø¤ÎŬÍÑ
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- NAIST-IS-MT351031
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- Ê¿²¬ ´§Æó
- NAIST-IS-MT351091
- Contextual Interpretation of Utterances in Relevance Theory
- Jun-ichi HIRASAWA
- NAIST-IS-MT351092
- ½¤»Î (Íý³Ø)
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- NAIST-IS-MT351202