- 開講元
- 情報理工学院
- 担当教員名
- TEUFEL SIMONE HEIDI
- 授業形態
- 講義
- メディア利用科目
- 曜日・時限(講義室)
- 集中講義等 3-8(W332)
- クラス
- -
- 科目コード
- XCO.T496
- 単位数
- 2
- 開講年度
- 2018年度
- 開講クォーター
- 1-2Q
- シラバス更新日
- 2018年8月6日
- 講義資料更新日
- 2018年8月31日
- 使用言語
- 英語
- アクセスランキング
-
media
講義の概要とねらい
This course who want to understand more about the linguistic forces that hold a text together beyond sentences. Master- Students with an interest in NLP are welcome in this class. The ideal participant in this course already has some background in general NLP, but beginners in NLP are also welcome. The topic covered concerns a quite specific set of tasks that go beyond basic NLP. However, all background information that is required to understand the main concepts treated in this course will be summarised in the first set of lectures+activities.
到達目標
Students will learn the theory of the core discourse phenomena (defined as all linguistic operations that add meaning beyond the single-sentence level), and NLP approaches to recognise these phenomena automatically in text. Exercises are an integral part of this intensive course. Students will experience the various analyses proposed in the literature themselves in first-hand in exercises, for instance by performing annotation exercises on real text, or by learning how to operationalise a theory into actual instructions. This way, they will encounter the level of ambiguity that is faced by automatic methods, rather than just seeing idealised examples chosen for illustrative purposes in the literature.
As a result, students who directly address discourse phenomena in their research should be able to put the new knowledge from this course into practice by creating more sophisticated automatic treatments of discourse phenomena. But students not directly working on discourse phenomena should also benefit. Background knowledge of discourse factors should help them
with the design of their own research work in related NLP applications (not treated here), such as information retrieval, sentiment detection, QA, summarisation, etc. All students, whatever their exact subjects, should hopefully profit by learning to design more meaningful evaluations of their NLP systems.
キーワード
topic segmentation, lexical chains, pronoun resolution, rhetorical relations, argumentation mining, discourse structure
学生が身につける力(ディグリー・ポリシー)
| ✔ 専門力 | ✔ 教養力 | コミュニケーション力 | 展開力(探究力又は設定力) | 展開力(実践力又は解決力) |
授業の進め方
The course is provided as an intensive course in late August. We alternate lectures and exercises
Students will be required to read one paper (8-15 pages) per topic (6 papers in total). Because the course is intensive, they should ideally do this reading before the course starts, at least for the first three topics covered. Reading will be provided well ahead of schedule.
授業計画・課題
| 授業計画 | 課題 | |
|---|---|---|
| 第1回 | Lecture1: Basics of NLP (1.5 h) | Specified in the class |
| 第2回 | Activity1: Basics of NLP (1.5 h) | |
| 第3回 | Lecture2: Topics and Topic Segmentation (1.5 h) | |
| 第4回 | Activity2: Topics and Topic Segmentation (1.5 h) | |
| 第5回 | Lecture3: Lexical Chains (1.5 h) | |
| 第6回 | Activity3: Lexical Chains (1.5 h) | |
| 第7回 | Lecture4: Pronoun Resolution (1.5 h) | |
| 第8回 | Activity4:Pronoun Resolution (1.5 h) | |
| 第9回 | Lecture5: Definite Noun Phrase Resolution and Information Status (1.5 h) | |
| 第10回 | Activity5: Definite Noun Phrase Resolution and Information Status (1.5 h) | |
| 第11回 | Lecture6: Rhetorical Relations (1.5 h) | |
| 第12回 | Activity6: Rhetorical Relations (1.5 h) | |
| 第13回 | Lecture7: Argumentation Mining (1.5 h) | |
| 第14回 | Activity7: Argumentation Mining (1.5 h) | |
| 第15回 | Exam |
教科書
Not specified.
参考書、講義資料等
Not specified.
成績評価の基準及び方法
A final exam will be conducted on all topics treated in the course.
関連する科目
- ART.T459 ： 自然言語処理
履修の条件(知識・技能・履修済科目等)
Those who want to understand more about the linguistic forces that hold a text together beyond sentences.
その他
One week intensive course in late August.
