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Using Wikipedia and Conceptual Graph Structures to Generate Questions for Academic Writing Support

Using Wikipedia and Conceptual Graph Structures to Generate Questions for Academic Writing Support. Presenter : Jian-Ren Chen Authors : Ming Liu, Rafael A. Calvo , Senior Member, IEEE , Anindito Aditomo , and Luiz Augusto Pizzato 2012 , TLT. Outlines. Motivation Objectives

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Using Wikipedia and Conceptual Graph Structures to Generate Questions for Academic Writing Support

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  1. Using Wikipedia and Conceptual Graph Structures to Generate Questions for Academic Writing Support Presenter : Jian-Ren ChenAuthors : Ming Liu, Rafael A. Calvo, Senior Member, IEEE, AninditoAditomo, and Luiz Augusto Pizzato 2012 , TLT

  2. Outlines • Motivation • Objectives • Architecture • Methodology • Experiments • Conclusions • Comments

  3. Motivation • Generic trigger questions have been widely used for literature review support. • creating specific questions • difficult • time consuming

  4. Objectives • The goal of our research is to develop a fullyautomated method to generate specific questions tosupport academic writing. • fullyautomated -> semiautomatic

  5. Architecture • Three key challenges of automatic trigger question generation for supporting writing. • identification of key/central concepts • Research Field、Technology、System、Term、Other • system’s lack of knowledge • Wikipedia • evaluate whether the questions generated by the system Social sciences are the fields of academic scholarship that study society. SOAP, originally defined as Simple Object Access Protocol, is a protocol specification for exchanging structured information in the implementation of web services in computer networks. An image retrieval system is a computer system for browsing, searching and retrieving images from a large database of digital images. The term cognitive load is used in cognitive psychology to illustrate the load related to the executive control of WM.

  6. Methodology-Framework

  7. Methodology VSM D1 = "I like databases" D2 = "I hate hate databases" Document-term matrix:

  8. Methodology • Key Phrase match • Wikipedia articles research field • articles retrieve • definition sentence • Tregex expression rules Data mining, a branch of computer science and artificial intelligence, is the process of extracting patterns from data. • classify the associated key phrase Research Field, Technology, System, Term, and Other

  9. Methodology 2. phrase list 1. target sentence: (Tregex expression rules) Ex: Apply-to: concept name + is|are + usedfor/in + Object Has-Limitation, and Has-Strength : concept name + overcome/address/+ a problem/limitation of something

  10. Methodology

  11. Methodology first triple with Is-a relation matches Rule 2: Latent Semantic Indexing is an indexing and retrieval method that uses a math... How do you see Latent semantic indexing being applied in your project? the second triple with an Apply-to relation and a phrase list as white node matches Rule 7: Do you know that Latent Semantic Indexing has been applied in Information Discovery, automated document Classification, and Text summarization? How are these applications of Latent Semantic Indexing relevant to your project?

  12. Experiments-Evaluation

  13. Experiments-Key Phrase Classification F-score: 0.790.860.70.8 “denial-of-service attack”: A denial-of-service attack (DoS attack) or distributed denial-of-service attack (DDoS attack) is an attempt to make a computer resource unavailable to its intended users. In pattern recognition and in image processing, feature extraction is a special formof dimensionality reduction. “Data mining, a branch of computer science andartificial intelligence, is the process of extracting patterns fromdata.” algorithm, collaboration, compiler, gray, measurement,ownership, research, goal, lingua franca, bought, andreview

  14. Experiments-Question Authorship Evaluation

  15. Experiments-Comparative Evaluation of Three Question Producers ANOVA: Fisher’s least significant difference (LSD): Computer VS Generic: QM3(MD(0.47)>LSD(0.23))and QM4(MD(0.33)>LSD(0.22)) Supervisor VS Generic: QM3(MD(0.35)>LSD(0.24))and QM4(MD(0.35)>LSD(0.23)) ComputerVS Supervisor : QM3(MD(0.12)>LSD(0.25))and QM4(MD(0.01)>LSD(0.24))

  16. Experiments-Correlation Analysis of Quality Measures

  17. Experiments-Investigation on the Impact of Computer Generated Questions by Groups

  18. Experiments-Relation Type Evaluation

  19. Conclusions • The computer-generated questions were perceived to be as pedagogically useful as human supervisorquestions, and more useful than generic questions. • The computer-generated questions were considered to be more useful by first-year students, compared tosecond and third year students.

  20. Comments • Advantages • Computer-generated questions is useful. • Disadvantage • it is domain dependent. • may not apply this approach to other applications. • Applications • Key Phrase Extractionand Classification • Automatic Question Generation

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