Machine Learning & Question Generation 2017


Notes:

  • Generative conversational model

Wikipedia:

See also:

Question Generation | Question Generation Module


Machine Comprehension by Text-to-Text Neural Question Generation
X Yuan, T Wang, C Gulcehre, A Sordoni… – arXiv preprint arXiv …, 2017 – arxiv.org
Machine Comprehension by Text-to-Text Neural Question Generation … 4) who became the ruling class of england? Table 1: Examples of conditional question generation given a context and an answer from the SQuAD dataset, using the scheme referred to as RPPL + QA below …

GuessWhat?! Visual object discovery through multi-modal dialogue
H De Vries, F Strub, S Chandar, O Pietquin… – Proc. of …, 2017 – openaccess.thecvf.com
… language pro- cessing [10]. Traditionally, dialogue systems have been built through heavy engineering and hand-crafted expert knowledge, despite machine learning attempts for almost two decades [23, 38]. One of the difficulties …

Deep reinforcement learning: An overview
Y Li – arXiv preprint arXiv:1701.07274, 2017 – arxiv.org
… Szepesvári, 2010; Bertsekas, 2012; Powell, 2011; Bertsekas and Tsitsiklis, 1996; Puterman, 2005; Littman, 2015; Kaelblingetal., 1996); deep learning (LeCunetal., 2015; Goodfellowetal., 2016; Bengio, 2009; DengandDong, 2014); machine learning (JordanandMitchell, 2015 …

Question answering and question generation as dual tasks
D Tang, N Duan, T Qin, M Zhou – arXiv preprint arXiv:1706.02027, 2017 – arxiv.org
Page 1. arXiv:1706.02027v1 [cs.CL] 7 Jun 2017 Question Answering and Question Generation as Dual Tasks Duyu … Abstract We study the problem of joint question answering (QA) and question generation (QG) in this paper. Our …

Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
M Joshi, E Choi, DS Weld, L Zettlemoyer – arXiv preprint arXiv:1705.03551, 2017 – arxiv.org
… and the Web. This decoupling of question generation from evidence collection allows us to control for potential bias in question style or content, while offering organi- cally generated questions from various topics. De- signed …

End-to-end optimization of goal-driven and visually grounded dialogue systems
F Strub, H De Vries, J Mary, B Piot, A Courville… – arXiv preprint arXiv …, 2017 – arxiv.org
… Page 3. Figure 4: Question generation model … This mainly reproduces baselines introduced in [de Vries et al., 2016]. Question generation baseline We split the questioner’s job into two different tasks: one for asking the questions and an- other one for guessing the object …

Automatic chinese factual question generation
M Liu, V Rus, L Liu – IEEE Transactions on Learning …, 2017 – ieeexplore.ieee.org
… Pro- fessor You [24] used an early version of LTP to develop a Chinese question generation system … to-Rank Learning to rank is a relatively new research area, which received increasing attention in both the Information Retrieval and Machine Learning research communities …

Speaking the same language: Matching machine to human captions by adversarial training
R Shetty, M Rohrbach, LA Hendricks… – Proceedings of the …, 2017 – openaccess.thecvf.com
… pleted. We note that generating diverse sentences is also a challenge in visual question generation, see concurrent work [19], and in language-only dialogue generation stud- ied in the linguistic community, see eg [23, 24]. When …

A Joint Model for Question Answering and Question Generation
T Wang, X Yuan, A Trischler – arXiv preprint arXiv:1706.01450, 2017 – arxiv.org
… Nat- ural language processing (almost) from scratch. The Journal of Machine Learning Research, 12:2493–2537, 2011 … Du, Xinya, Shao, Junru, and Cardie, Claire. Learning to ask: Neural question generation for reading comprehen- sion …

VQABQ: visual question answering by basic questions
JH Huang, M Alfadly, B Ghanem – arXiv preprint arXiv:1703.06492, 2017 – arxiv.org
… Our method involves in different areas in machine learning, nat- ural language processing (NLP) and computer vision … In [24], they exploit RNN and Convolutional Neural Network (CNN) to build a question generation algorithm, but the generated question sometimes has invalid …

Cognitive analytics driven personalized learning
VN Gudivada – Educational Technology, 2017 – JSTOR
… A Screenshot of our prototype automated question generation system for set operations is shown in Figure 1 … This layer also provides machine learning and artificial intelligence libraries. The first three layers are infrastructural components and can be used in other …

Lc-quad: A corpus for complex question answering over knowledge graphs
P Trivedi, G Maheshwari, M Dubey… – International Semantic Web …, 2017 – Springer
… existing datasets are insufficient in terms of size, variety or complexity to apply and evaluate a range of machine learning based QA … We frame our question generation problem as a transduction problem, similar to [10], in which KB subgraphs generated by the seed entity are …

Question asking as program generation
A Rothe, BM Lake, T Gureckis – Advances in Neural Information …, 2017 – papers.nips.cc
… Although impressive, most work on active machine learning has focused on relatively simple types of information requests (most often a request for a … The Visual Question Generation (VQG) data set [16] contains images paired with interesting, human-generated questions …

ShapeWorld-A new test methodology for multimodal language understanding
A Kuhnle, A Copestake – arXiv preprint arXiv:1704.04517, 2017 – arxiv.org
… is that the learning process and decisions of deep networks are more difficult to interpret than shal- lower machine learning methods … experiments in which parts of the data are artificial and/or generated automatically, for instance, automatic question generation from annotation …

Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications
J Tetreault, J Burstein, C Leacock… – Proceedings of the 12th …, 2017 – aclweb.org
… Combining Textual and Speech Features in the NLI Task Using State-of-the-Art Machine Learning Tech- niques Pavel Ircing, Jan Svec, Zbynek Zajic, Barbora Hladka and Martin … Multiple Choice Question Generation Utilizing An Ontology Katherine Stasaski and Marti A. Hearst …

Automatically generating effective search queries directly from community question-answering questions for finding related questions
A Figueroa – Expert Systems with Applications, 2017 – Elsevier
… This was the germ of the idea of Zhao et al. (2011), who automatically generated questions from queries for cQA. Fundamentally, their method gathered query-to-question pairs from web search logs, whereby question generation templates were acquired …

Automated generation of assessment tests from domain ontologies
V EV, PS Kumar – Semantic Web, 2017 – content.iospress.com
… E-mails: vinuev@cse.iitm.ac.in, mvsquare1729@gmail.com. Keywords: MCQ generation, question generation, ontologies, e-learning system, Item Response Theory, MCQ difficulty-level … But, having a question generation module does not fully resolve the underlying problem …

Automatic chinese multiple choice question generation using mixed similarity strategy
M Liu, V Rus, L Liu – IEEE Transactions on Learning …, 2017 – ieeexplore.ieee.org
… The most relevant work to ours is the Chinese multiple choice question generation system developed by Xiang and Gu, who used an … Specifically, the major contribu- tions of this paper are the following: • Applied a machine learning approach to the task of generating Chinese …

Overcoming barriers to educational analytics: How systems thinking and pragmatism can help
LP Macfadyen – Educational Technology, 2017 – JSTOR
… aspx . Nielsen, R., Buckingham, J., Knoll, G., Marsh, B., & Palen, L. (2008). A taxonomy of questions for question generation. In Workshop on the Question Generation Shared Task and Evaluation Challenge … Piwek, P., & Boyer, KE (2012). Special issue on question generation …

Visual reference resolution using attention memory for visual dialog
PH Seo, A Lehrmann, B Han, L Sigal – Advances in neural …, 2017 – papers.nips.cc
… During question generation, the target digits for a question is selected based on a subset of the previous targets referred to by ambiguous expressions, as shown in Figure 1. For ease of evaluation, we generate a single word answer rather than a sentence for each question and …

Improving sentiment analysis with document-level semantic relationships from rhetoric discourse structures
J Märkle-Huß, S Feuerriegel… – … of the 50th …, 2017 – hl-128-171-57-22.library.manoa …
… Accordingly, this paper proposes a novel combination of weighting and grid search to aggregate sentiment scores from the RST tree, as well as feature engi- neering for machine learning … 3.4. Feature engineering for machine learning …

Reinforced mnemonic reader for machine comprehension
M Hu, Y Peng, X Qiu – CoRR, abs/1705.02798, 2017 – pdfs.semanticscholar.org
Page 1. Reinforced Mnemonic Reader for Machine Comprehension Minghao Hu? Yuxing Peng School of Computer Science National University of Defense Technology {huminghao09,yxpeng}@nudt.edu.cn Xipeng Qiu School …

Data augmentation for visual question answering
K Kafle, M Yousefhussien, C Kanan – Proceedings of the 10th …, 2017 – aclweb.org
… Visual question generation was also studied in (Mostafazadeh et al., 2016), with an emphasis on generating questions about images that are beyond the literal visual content of the im- age … In International Con- ference on Machine Learning (ICML) …

Attentive listening system with backchanneling, response generation and flexible turn-taking
D Lala, P Milhorat, K Inoue, M Ishida… – Proceedings of the 18th …, 2017 – aclweb.org
… There have been many works on automatic backchan- nel generation, with most using prosodic features for either rule-based models (Ward and Tsukahara, 2000; Truong et al., 2010) or machine learning methods (Morency et al., 2008; Ozkan et al., 2010; Kawahara et al., 2015 …

Robustness Analysis of Visual QA Models by Basic Questions
JH Huang, M Alfadly, B Ghanem – arXiv preprint arXiv:1709.04625, 2017 – arxiv.org
… Our VQABQ method involves in different areas in Machine Learning, Natural Language Processing (NLP) and Computer Vision … In (Ren, Kiros, and Zemel 2015), they exploit RNN and Convolutional Neu- ral Network (CNN) to build a question generation algorithm, but the …

A cognitive system for business and technical support: A case study
P Dhoolia, P Chugh, P Costa… – IBM Journal of …, 2017 – ieeexplore.ieee.org
… Assist components, which uses the IBM Watson à Natural Language Classifier (NLC) service [14]—a service based on machine learning [15] and … the problem description, and if a match is found, then we generate a question based on a standard question generation template …

Video Question Answering via Gradually Refined Attention over Appearance and Motion
D Xu, Z Zhao, J Xiao, F Wu, H Zhang, X He… – Proceedings of the 2017 …, 2017 – dl.acm.org
Page 1. Video Question Answering via Gradually Refined Attention over Appearance and Motion? Dejing Xu‡, Zhou Zhao‡, Jun Xiao‡, Fei Wu‡, Hanwang Zhang§, Xiangnan He¶, Yueting Zhuang‡ ‡Zhejiang University, §Columbia …

MLP-GA based algorithm to detect application layer DDoS attack
KJ Singh, T De – Journal of Information Security and Applications, 2017 – Elsevier
… The shared goal of the Turing test module is to challenge the sender to response for a correct answer to the text based question generated by the question generation module. Classification algorithms play a vital role for effective classification of data sets …

Machine Learning Approach to the Process of Question Generation
M Blšták, V Rozinajová – International Conference on Text, Speech, and …, 2017 – Springer
Abstract In this paper, we introduce an interactive approach to generation of factual questions from unstructured text. Our proposed framework transforms input text into structured set of features and uses them for question generation. Its learning process is

Large-Scale Simple Question Generation by Template-Based Seq2seq Learning
T Liu, B Wei, B Chang, Z Sui – National CCF Conference on Natural …, 2017 – Springer
… Brevdo, E., Chen, Z., Citro, C., Corrado, G., Davis, A., Dean, J., Devin, M., et al.: TensorFlow: large-scale machine learning on heterogeneous … 10.1007/978-3-662-44848-9_11 Google Scholar. 6. Du, X., Shao, J., Cardie, C.: Learning to ask: neural question generation for reading …

Unsupervised Learning of Question Difficulty Levels Using Assessment Responses
S Narayanan, VS Kommuri, NS Subramanian… – … Science and Its …, 2017 – Springer
… of the difficulty levels in question banks offers a wide range of benefits apart from higher assessment quality: improved personalized learning, adaptive testing, automated question generation, and cheating detection. Adopting unsupervised machine learning techniques, we …

An Elevator Pitch on Deep Learning
YT Hu, AG Schwing – GetMobile: Mobile Computing and …, 2017 – dl.acm.org
… Machine learning refers to techniques for adjusting the parameters w, ie, for using the model may perform well on the training set and poorly on the test set … (b) Visual question generation. Given an input image, the model is able to generate a diverse set of questions …

The Algorithmic Inflection of Russian and Generation of Grammatically Correct Text
TM Sadykov, TA Zhukov – arXiv preprint arXiv:1706.02551, 2017 – arxiv.org
… Towards topic-to-question generation, Computational Linguistics, 41:1 (2015), 20p … Natural language processing as a source of linguistic knowledge, Proceedings of the International Conference on Machine Learning, Models, Technologies and Applications (2003), 68-74 …

Asking the Difficult Questions: Goal-Oriented Visual Question Generation via Intermediate Rewards
J Zhang, Q Wu, C Shen, J Zhang, J Lu… – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. Asking the Difficult Questions: Goal-Oriented Visual Question Generation via Intermediate Rewards … Voltaire Although Visual Question Answering (VQA) [3, 30, 31] has attracted more attention, Visual Question Generation (VQG) is a much more difficult task …

A conceptual review of Automatic Question Generation from a given Punjabi Text
AS Gill, G kaur Virk, A Bhandari – 2017 – ijetsr.com
… Natural language processing (almost) from scratch. Journal of Machine Learning Research, 12(Aug), 2493- 2537. 5. Garg, P., & Bedi, ECS (2014, August). A Review on Question Generation System from Punjabi Text. International …

Incomplete Follow-up Question Resolution using Retrieval based Sequence to Sequence Learning
V Kumar, S Joshi – Proceedings of the 40th International ACM SIGIR …, 2017 – dl.acm.org
… re-training the model by keeping some parameters xed on low resource language pair. However, it is not clear to us how this ap- proach can be applied to the task of complete question generation from an incomplete follow-up question …

Identifying where to focus in reading comprehension for neural question generation
X Du, C Cardie – Proceedings of the 2017 Conference on Empirical …, 2017 – aclweb.org
… Natural language processing (almost) from scratch. Journal of Machine Learning Research 12(Aug):2493–2537. Michael Denkowski and Alon Lavie … Xinya Du, Junru Shao, and Claire Cardie. 2017. Learn- ing to ask: Neural question generation for reading comprehension …

Neural Joke Generation
H Ren, Q Yang – stanford.edu
… with Long Short Term Memory (LSTM), are having successful applications in a wide range of machine learning problems that … The architecture of question generation [12] includes an attention mechanism on the encoder representation to generate the associated question Q to …

Inaugural Course Project Poster Fair
N Yazdani – pdfs.semanticscholar.org
… you relevant questions like “What are you studying?” or “When are you graduating?” Previous work in question generation has focused … On the contrary, we believe that informed feature selection, modern machine learning methods, and large amounts of sequential data, can be …

Learning Semantic Patterns for Question Generation and Question Answering
HP Rodrigues – 2017 – pdfs.semanticscholar.org
… In this chapter we overview the work done in Question Answering (QA) – Section 3.1 – and Question Generation (QG) – Section 3.2 –, giving special attention to approaches that use … a machine learning-based named entity recognizer. Just.Ask also has an pattern learning …

Dataset for the First Evaluation on Chinese Machine Reading Comprehension
Y Cui, T Liu, Z Chen, W Ma, S Wang, G Hu – arXiv preprint arXiv …, 2017 – arxiv.org
… 5Full descriptions of abbreviations can be found at http:// www.ltp-cloud.com/intro/en/#dp_how. 3.4.2. User Query RC Unlike the cloze dataset, we have no automatic question generation procedure in this type … Journal of Machine Learning Research, 15(1):1929–1958 …

Progress in building a machine that can ask interesting and informative questions
A Rothe, B Lake, T Gureckis – pdfs.semanticscholar.org
… In comparison, machine learning systems that attempt to mimic this ability are still extremely limited (eg, current chatbots ask questions based on preprogrammed routines). In the present work, we developed a computational model of question generation …

Hi, how can I help you?: Automating enterprise IT support help desks
S Mani, N Gantayat, R Aralikatte, M Gupta… – arXiv preprint arXiv …, 2017 – arxiv.org
… [Cortes and Vapnik 1995] Cortes, C., and Vapnik, V. 1995. Support-vector networks. Machine learning 20(3):273–297 … Extracting simplified statements for factual question generation. In Proceedings of QG2010: The Third Workshop on Ques-tion Generation, 11 …

Domain Specific Automatic Question Generation from Text
K Soleymanzadeh – Proceedings of ACL 2017, Student Research …, 2017 – aclweb.org
… Due to the need for an SRL system in semantic question generation systems, we plan to design a supervised SRL system. Supervised, unsupervised and semi-supervised machine learning methods are applied in building SRL systems …

Plan, Attend, Generate: Planning for Sequence-to-Sequence Models
F Dutil, C Gulcehre, A Trischler… – arXiv preprint arXiv …, 2017 – papers.nips.cc
… 9 Page 10. Conference on Machine Learning. pages 2048–2057. Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016 … 2017. Machine comprehension by text-to-text neural question generation. arXiv preprint arXiv:1705.02012 . 10

Construction and Application of Mathematical Model Based on Intelligent Test Paper Generation Algorithm
J Zhang – Revista de la Facultad de Ingeniería, 2017 – revistadelafacultaddeingenieria.com
… Jouault, C., Seta, K., & Hayashi, Y. (2016). Content-Dependent Question Generation using LOD for History Learning in Open Learning Space … Medical Prognosis Generation from General Blood Test Results Using Knowledge-Based and Machine-Learning-Based Approaches …

Automatic Neural Question Generation using Community-based Question Answering Systems
T Baghaee – 2017 – uleth.ca
… as well as other work on this problem. We define the question generation task and describe … from past experiences and conceive the world around them as a hierarchy of concepts. To elaborate, deep learning is a machine learning approach that simplifies working with …

Factual open cloze question generation for assessment of learner’s knowledge
B Das, M Majumder – International Journal of Educational Technology in …, 2017 – Springer
… Correia et al. used supervised machine learning technique for selecting stem to generate cloze question … Silveira described a general framework for question generation. The input to the system was free text, which was parsed and annotated with metadata …

A Review On Generative Conversational Model
E Varghese, MTR Pillai – data.conferenceworld.in
… Alternate one is the smart machine based work, where they use machine learning to do work and can learn on their own. While planning a framework for chatbot, we have to … This system has three sections Plain text extraction Question generation and Question and answers …

Automatic generation of multiple choice questions for e-assessment
A Santhanavijayan… – … Journal of Signal …, 2017 – inderscienceonline.com
… His current research areas of interests include e-learning assessment, image processing, data mining, machine learning, and natural … His current areas of interests include natural language processing, e-learning, e-assessment, automatic question generation, and data mining …

Variational Attention for Sequence-to-Sequence Models
H Bahuleyan, L Mou, O Vechtomova… – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. Variational Attention for Sequence-to-Sequence Models Hareesh Bahuleyan?, Lili Mou?, Olga Vechtomova, Pascal Poupart University of Waterloo, ON, Canada {hpallika, ovechtomova, ppoupart}@uwaterloo.ca, doublepower.mou@gmail.com Abstract …

Joint Learning of Response Ranking and Next Utterance Suggestion in Human-Computer Conversation System
R Yan, D Zhao – Proceedings of the 40th International ACM SIGIR …, 2017 – dl.acm.org
Page 1. Joint Learning of Response Ranking and Next Utterance Suggestion in Human-Computer Conversation System Rui Yan †,? 1 Institute of Computer Science and Technology Peking University Beijing 100871, China ruiyan@pku.edu.cn …

Co-attending Free-form Regions and Detections with Multi-modal Multiplicative Feature Embedding for Visual Question Answering
P Lu, H Li, W Zhang, J Wang, X Wang – arXiv preprint arXiv:1711.06794, 2017 – arxiv.org
… intelligence. Great progress has been achieved for different tasks in- cluding image captioning (Karpathy and Fei-Fei 2015), vi- sual question generation (Mostafazadeh et al. 2016; Li et al. 2017b), video question answering (Ye et al …

Text, Speech, and Dialogue: 20th International Conference, Tsd 2017, Prague, Czech Republic, August 27-31, 2017, Proceedings
K Ekštein, V Matoušek – 2017 – books.google.com
… Page 17. XVIII Contents Machine Learning Approach to the Process of Question Generation….. 102 Miroslav Blšták and Viera Rozinajová Automatic Extraction of Typological Linguistic Features from Descriptive Grammars …

Learning by Asking Questions
I Misra, R Girshick, R Fergus, M Hebert, A Gupta… – arXiv preprint arXiv …, 2017 – arxiv.org
… 1. Introduction Machine learning models have led to remarkable progress in visual recognition. However … architecture. Visual question generation (VQG) was recently pro- posed as an alternative to image captioning [33, 36, 40] …

Automated Quiz Generator
A Bongir, V Attar, R Janardhanan – The International Symposium on …, 2017 – Springer
… 1.2 Ranking Generated Questions. Heilman’s question generation (QG) system uses an Overgenerate-and-Rank Framework [HS09] for question generation … They make use of unigram, linguistic and entity features for their machine learning based interestingness ranker …

High-Order Attention Models for Visual Question Answering
I Schwartz, A Schwing, T Hazan – Advances in Neural Information …, 2017 – papers.nips.cc
… The quest for algorithms which enable cognitive abilities is an important part of machine learning and appears in many facets, eg, in visual question answering tasks [6], image captioning [26], visual question generation [18, 10] and machine comprehension [8]. A common trait in …

Building a Cognitive Application Using Watson DeepQA
C Asakiewicz, EA Stohr, S Mahajan, L Pandey – IT Professional, 2017 – ieeexplore.ieee.org
… A simple ontology was developed to guide question generation … to return the best-matching classes for a sentence or phrase Retrieve and Rank Helps users find the most relevant information for their query using a combination of search and machine learning algorithms to …

How to Revert Question Answering on Knowledge Graphs
G Maheshwari, M Dubey, P Trivedi, J Lehmann – researchgate.net
… numerous question answering (QA) approaches for knowledge graphs have been devised (see [4]). Many of them rely on machine learning techniques, which … We now describe how we reverse engineered the architecture of AskNow[3] to create a question generation framework …

Plan, Attend, Generate: Character-Level Neural Machine Translation with Planning
C Gulcehre, F Dutil, A Trischler, Y Bengio – Proceedings of the 2nd …, 2017 – aclweb.org
… (r)PAG approach empirically improves alignments over long input sequences. We demonstrated our models’ capabilities through results on character-level machine translation, an algorithmic task, and question generation … Machine learning 8(3-4):229–256. 233 Page 7 …

A Proposed Framework for Generating Random Objective Exams using Paragraphs of Electronic Courses
EE AbdElrazek – INTERNATIONAL JOURNAL OF …, 2017 – pdfs.semanticscholar.org
… The proposed question generation subsystem uses the open natural language processing (NLP) tool at this stage, which is a java library for processing natural text, based on machine learning tools; it supports variety of natural language processing tasks such as the following …

Video Question Answering Using a Forget Memory Network
Y Ge, Y Xu, Y Han – CCF Chinese Conference on Computer Vision, 2017 – Springer
… statistical ranking for question generation. In: Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp. 609–617 … In: International Conference on Machine Learning, pp …

Distractor Generation with Generative Adversarial Nets for Automatically Creating Fill-in-the-blank Questions
C Liang, X Yang, D Wham, B Pursel… – Proceedings of the …, 2017 – dl.acm.org
… Automatic fill-in-the-blank question generation (FITB-QG) is a promising research area and a successful system would permit faster and less expensive question creation on a large scale … The proposed machine learning-based approach is fundamentally different from …

Keyword-based Query Comprehending via Multiple Optimized-Demand Augmentation
B Pan, H Li, Z Zhao, D Cai, X He – arXiv preprint arXiv:1711.00179, 2017 – arxiv.org
Page 1. Keyword-based ery Comprehending via Multiple Optimized-Demand Augmentation Boyuan Pan?, Hao Li?, Zhou Zhao†, Deng Cai?, Xiaofei He? ?State Key Lab of CAD&CG, College of Computer Science, Zhejiang …

Robustness Analysis of Visual Question Answering Models by Basic Questions
JH Huang – 2017 – repository.kaust.edu.sa
… Our VQABQ method involves in different areas in Machine Learning, Natural Language Processing (NLP) and Computer Vision … In [16], they exploit RNN and Convolutional Neural Network (CNN) to build a question generation algorithm …

The Achievement of Higher Flexibility in Multiple Choice-based Tests Using Image Classification Techniques
M Afifi, KF Hussain – arXiv preprint arXiv:1711.00972, 2017 – arxiv.org
… In this work, however, we have shown that by using a more sophisticated machine learning-based approach, high accurate OMR systems can be developed without any restrictions … 4] M. Liu, V. Rus, and L. Liu, “Automatic chinese multiple choice question generation using mixed …

Big Media Data Analysis
A Iosifidis, A Tefas, I Pitas, M Gabbouj – 2017 – Elsevier
… While the size of data being available everyday becomes enormously big, their practical value for applying machine learning models is … Existing datasets target the problems of generic object and scene analysis [[80]; [81] ; [82]], visual question generation and answering [[83 …

Accessing Government Open Data Through Chatbots
S Porreca, F Leotta, M Mecella, S Vassos… – … Conference on Web …, 2017 – Springer
… have to be not trivially combined, including pattern matching, parsing, artificial intelligence, machine learning, and ontologies … using a “Overgenerating Transformations and Rankings” algorithm, which was implemented using the question generation framework presented in [5 …

A Survey Of Various Chatbot Implementation Techniques
A Deshpande, A Shahane, D Gadre, M Deshpande… – pdfs.semanticscholar.org
… Once the user has entered the query, the chatbot sends it to the machine learning NLP (Natural Language Processing) Engine … The proposed system has three phases Plain text extraction, Question Generation and Question and Answers …

Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder
C Gulcehre, F Dutil, A Trischler, Y Bengio – arXiv preprint arXiv …, 2017 – arxiv.org
… We demonstrated our models’ capabilities through results on character-level machine translation, an algorithmic task, and question generation. In machine translation, models with planning outperform a state-of-the-art baseline on … Machine learning 8(3-4):229–256. Page 7 …

Social and Ethical Impact of Artificial Intelligence on Public-A Case Study of University Students
FF Quraishi, SA Wajid, P Dhiman – 2017 – ijsrset.com
… Various machine learning techniques can be applied to medical image data … Jonathan C. Brown, Gwen A. Frishkoff , and Maxine Eskenazi, “Automatic Question Generation for Vocabulary Assessment,” Proceedings of Human Language Technology Conference and Conference …

Chatbots as a Novel Access Method for Government Open Data?
S Porreca, F Leotta, M Mecella, T Catarci – ceur-ws.org
… have to be not trivially combined, including pattern matching, parsing, artificial intel- ligence, machine learning, and ontologies … using a “Overgenerating Transformations and Rankings” algorithm, which was imple- mented using the question generation framework presented in [5 …

Measures To Calculate Semantic Similarity: A Survey
T Lohnari – pdfs.semanticscholar.org
… for tasks such as text summarization [14], text classification [15], redundancy removal, document retrieval [16], question generation, question answering [17 … The two texts that are to be compared are converted into weighted vectors of concepts by employing machine learning …

Keynote Talk
E Haji?ová, T Haderlein, A Schützenberger… – repo.pw.edu.pl
… Synthesis . . . . . 92 Raheel Qader, Gwénolé Lecorvé, Damien Lolive, Marie Tahon, and Pascale Sébillot Page 2. Machine Learning Approach to the Process of Question Generation . . . . . 102 Miroslav Blšták and Viera Rozinajová …

Motivation and research in architectural intelligent tutoring
K Brawner, AM Sinatra… – International Journal of …, 2017 – inderscienceonline.com
… holds an MS and PhD in Computer Engineering with a focus on Intelligent Systems and Machine Learning (ML) from … Assessing questions can be automatically generated through question generation techniques which generate multiple choice questions and distracters (Olney …

Plan, attend, generate: Planning for sequence-to-sequence models
C Gulcehre, F Dutil, A Trischler… – Advances in Neural …, 2017 – papers.nips.cc
… 9 Page 10. Conference on Machine Learning. pages 2048–2057. Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016 … 2017. Machine comprehension by text-to-text neural question generation. arXiv preprint arXiv:1705.02012 . 10

Introspection Planning: Representing Metacognitive Experience
ROP Edwards – cc.gatech.edu
… gle questions (Oehlmann, Edwards, & Sleeman 1994). Question generation is achieved by execut- ing actions organised in a question plan which access components of a sentence and combine … Learning. In: Michalski, R., & Tecuci, G. (Eds.) Machine Learning: A Multistrategy …

Role of Premises in Visual Question Answering
A Mahendru – 2017 – vtechworks.lib.vt.edu
… Master of Science in Computer Engineering Dhruv Batra, Chair Devi Parikh Bert Huang April 10, 2017 Blacksburg, Virginia Keywords: Machine Learning, Natural language Processing, Computer Vision Copyright 2017, Aroma Mahendru Page 2 … 15 6.1 Question Generation …

Evaluating the quality of the ontology-based auto-generated questions
MN Demaidi, MM Gaber, N Filer – Smart Learning Environments, 2017 – Springer
… questions. This will provide guidance for developers and researchers working in the field of ontology-based question generators, and help building a prediction model using machine learning techniques. Keywords. Ontology …

Addressing student misinterpretations of story problems in MAST
N Khodeir, N Wanas, H Elazhary… – … (ACCS) Systems & …, 2017 – ieeexplore.ieee.org
… 13, pp. 159-169, 2003. [2] R. Sison and M. Shimura, “Student modeling and machine learning,” Artificial Intelligence in Education, vol. 9, no. 3, pp. 128-158, 1998 … 555-562, 2009. [10] P. Piwek and S. Stoyanchev, “Question generation in the CODA project,” Proceedings of the …

The Art of Deep Connection-Towards Natural and Pragmatic Conversational Agent Interactions
A Ray – 2017 – vtechworks.lib.vt.edu
… A user secretly imagines an image, and our machine learning model tries to guess the scene by asking the user a limited set of informative questions in sequence, in turn filtering the set of images based on the user answer at each step … Question generation …

An Interactive Tour Guide for a Heritage Site
S Chelaramani, V Muthireddy… – Proceedings of the …, 2017 – openaccess.thecvf.com
… Active learning methods have been gaining increased interest in the machine learning community [8, 4]. Ac- tive learning has found applications in a variety of sub- disciplines of NLP, such as information extraction, text clas- sification and natural language … Question Generation …

Learning Algorithms for Broad-Coverage Semantic Parsing
S Swayamdipta – 2017 – cs.cmu.edu
… Hence, I propose to return to it at the conclusion of the thesis. Thesis Statement: This thesis improves the quality of stand-alone broad-coverage semantic graph parsing by bring- ing together linguistic knowledge and new machine learning techniques …

Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
M Lapata, P Blunsom, A Koller – Proceedings of the 15th Conference of …, 2017 – aclweb.org
… His research is in statistical machine learning, involving proba- bilistic topic models, Bayesian nonparametric methods, and approximate posterior … Natural Language Question-Answer Pairs from a Knowledge Graph Using a RNN Based Question Generation Model Sathish …

Conversational Exploratory Search via Interactive Storytelling
S Vakulenko, I Markov, M de Rijke – arXiv preprint arXiv:1709.05298, 2017 – arxiv.org
… RQ4.2. Question generation: How to verify user understanding, satisfaction and preferences … 2017. “Let me convince you to buy my product … “. In Proceedings of Workshop on Machine Learning for Creativity, SIGKDD, Nova Scotia, Canada, August 2017 (ML4Creativity 17) …

Difficulty-level Modeling of Ontology-based Factual Questions
VEV, PS Kumar – arXiv preprint arXiv:1709.00670, 2017 – arxiv.org
… Traditionally, question generation (QG) ap- proaches have largely focused on retrieving ques- tions from raw text, databases and other non- semantics based data sources … With the help of standard feature selection methods in machine learning and by using a test dataset, we …

An Efficient Approach for Keyphrase Extraction from English Document
IH Emu, AU Ahmed, MM Islam, MS Al Mamun… – 2017 – mecs-press.org
… Many research articles have been found in the literature for keyphrase extraction used machine learning or data mining approaches [23-31] … [23] Pabitha, P., Suganthi, S. and Ram, R.,. “Key Phrase Extraction Using Naive Bayes? in Question Generation System”, Asian Journal …

Automatic question generation for virtual humans
EL Fasya – 2017 – essay.utwente.nl
Page 1. AUTOMATIC QUESTION GENERATION FOR VIRTUAL HUMANS Evania Lina Fasya … This research aims to prepare the domain knowledge of Alice in a more automated process by developing an automatic question generation system. The system is called Alice …

Incorporating External Knowledge to Answer Open-Domain Visual Questions with Dynamic Memory Networks
G Li, H Su, W Zhu – arXiv preprint arXiv:1712.00733, 2017 – arxiv.org
… 4.1.2 Open-domain Question Generation In this paper, we automatically generate numerous question-answer pairs by considering the image content and relevant background knowledge, which provides a test bed for the evaluation of a more realistic VQA task …

Which is the Effective Way for Gaokao: Information Retrieval or Neural Networks?
S Guo, X Zeng, S He, K Liu, J Zhao – … of the 15th Conference of the …, 2017 – aclweb.org
Page 1. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 111–120, Valencia, Spain, April 3-7, 2017. cO2017 Association for Computational Linguistics …

Enhancing The Security Of Secondary Authentication System Based On Event Logger
P Sonawane, A Augustine – ijcea.com
… Keywords: Secondary Authentication, Smart phone data , RSA, Machine learning. [1] INTRODUCTION Secondary Authentication can be categorized in 2 types … question generation. The client app fetches all the data From Event Extraction As shown in figure 1. 3.1.3 Server …

Modeling a Peer Assessment Framework by Means of a Lazy Learning Approach
M De Marsico, A Sterbini, F Sciarrone… – … Symposium on Emerging …, 2017 – Springer
… 263–272. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-25813-8_28 CrossRefGoogle Scholar. 6. Hoshino, A., Nakagawa, H.: A real-time multiple-choice question generation for language testing – a preliminary study … Mitchell, TM: Machine Learning, 1st edn …

Introduction To Assessment Methods & Gift
RA Sottilare, AC Graesser, X Hu, GA Goodwin – … for Intelligent Tutoring … – gifttutoring.org
… Future expert workshops are planned for machine learning tech- niques, potential standards, and learning effect evaluation methods … Rus, V. & Graesser, AC (Eds.)(2009). The Question Generation Shared Task and Evaluation Challenge. Retrieved from http://www …

Product review summarization through question retrieval and diversification
M Liu, Y Fang, AG Choulos, DH Park, X Hu – Information Retrieval Journal, 2017 – Springer
… review. 2.3 Question generation. Our problem also relates to automatic question generation (AQG) from text data. It is a challenging task as it involves natural language understanding and generation (Rus and Arthur 2009). Most …

Abstractive Text Summarization Using Deep Learning
CX Tran – 2017 – dspace.jaist.ac.jp
Page 1. Japan Advanced Institute of Science and Technology JAIST Repository https://dspace.jaist.ac.jp/ Title Abstractive Text Summarization Using Deep Learning Author(s) Tran, Chien Xuan Citation Issue Date 2017-06 Type Thesis or Dissertation Text version author …

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
R Barzilay, MY Kan – Proceedings of the 55th Annual Meeting of the …, 2017 – aclweb.org
… and Interactive Systems Area) Alexandra Balahur (Sentiment Analysis and Opinion Mining Area) Mohit Bansal (Vision, Robotics and Grounding Area) Chia-Hui Chang (Information Extraction and NLP Applications Area) Grzegorz Chrupa?a (Machine Learning Area) Mona Diab …

A Big Data architecture for knowledge discovery in PubMed articles
F Gargiulo, S Silvestri, M Ciampi – … and Communications (ISCC) …, 2017 – ieeexplore.ieee.org
… they focused on the analysis and preprocessing of Big Data natural language texts, namely tweets, for NLP and machine learning applications such … Its aim is to provide a search tool aid based on automatic question generation suggestions, obtained from basic search terms of …

Building and querying an enterprise knowledge graph
D Song, F Schilder, S Hertz, G Saltini… – IEEE Transactions …, 2017 – ieeexplore.ieee.org
… The core of this approach is a machine learning classifier that predicts the probability of a possible relationship for a given … As the question generation proceeds, our system finds sug- gestions based on the discovered question segments, and produces the following sequence of …

Design Recommendations for Intelligent Tutoring System-Volume 5: Assessment Methods
R Sottilare, A Graesser, X Hu, G Goodwin – 2017 – books.google.com
… Future expert workshops are planned for machine learning tech- niques, potential standards, and learning effect evaluation methods … Rus, V. & Graesser, AC (Eds.)(2009). The Question Generation Shared Task and Evaluation Challenge. Retrieved from http://www …

Improving the integrated experience of in-class activities and fine-grained data collection for analysis in a blended learning class
Y Shin, J Park, S Lee – Interactive Learning Environments, 2017 – Taylor & Francis

ClaimBuster: the first-ever end-to-end fact-checking system
N Hassan, G Zhang, F Arslan, J Caraballo… – Proceedings of the …, 2017 – dl.acm.org
… Starting in December 2014, we have been building ClaimBuster, an end-to-end system that uses machine learning, natural language processing, and … With regard to knowledge bases, it uses a question generation tool [6] to generate many questions based on the claim and …

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
M Palmer, R Hwa, S Riedel – Proceedings of the 2017 Conference on …, 2017 – aclweb.org
… Machine Learning Mohit Bansal, UNC Chapel Hill Jordan Boyd-Graber, University of Colorado Trevor Cohn, University of Melbourne Hal Daumé, University of Maryland Alona Fyshe, University of Victoria Anoop Sarkar, Simon Fraser University …

Adaptively selecting biology questions generated from a semantic network
L Zhang, K VanLehn – Interactive Learning Environments, 2017 – Taylor & Francis
… order. ARTICLE HISTORY Received 16 December 2015 Accepted 14 May 2016 KEYWORDS Adaptive learning; question generation; student modeling; adaptive test items selection; Bayesian Knowledge Tracing 1. Introduction …

Authentication approach using one-time challenge generation based on user behavior patterns captured in transactional data sets
K Skra?i?, P Pale, Z Kostanj?ar – Computers & Security, 2017 – Elsevier
… We note that Nosseir et al. aimed to automate question generation by using the social network analysis technique developed by Streeter (1992). The following three questions were used to authenticate group users. • Who is the most active member? • …

Unifying the Video and Question Attentions for Open-Ended Video Question Answering
H Xue, Z Zhao, D Cai – IEEE Transactions on Image Processing, 2017 – ieeexplore.ieee.org
… The open-ended answers enable wider applications compared with the common multiple-choice tasks in Visual-QA. We first propose a data set for open-ended Video-QA with the automatic question generation approaches …

Data Science Solution for User Authentication
A Ibrahim – 2017 – ir.lib.uwo.ca
… 20 3.2.3 Adaptable Mechanism and Machine Learning ….. 22 … Furthermore, chapter 3 discusses about the adaptable mechanisms and machine learning techniques that will be used to build up knowledge and classify profiles …

Reflections on Serious Games
AC Graesser – Instructional Techniques to Facilitate Learning and …, 2017 – Springer
… accuracy of the assessment improves over time with feedback from the performance, using modern machine learning methods that … time on task, student generation of information, receiving accurate discriminations, amount of scaffolding, student question generation, reading text …

Experiments in neural question answering
RA Islam – 2017 – uleth.ca
… information about the structure and meaning of the sentences. These information can be learned from large amounts of data using machine learning models (Kusner et al., 2015). 1https://en.wikipedia.org/wiki/Cosine similarity 6 Page 17. 2.3. WORD EMBEDDING …

Helping Users Understand Privacy Notices with Automated Query Answering Functionality: An Exploratory Study
KM Sathyendra, A Ravichander, PG Story… – 2017 – reports-archive.adm.cs.cmu.edu
… These efforts show the promise of machine learning and natural language pro- cessing when it comes to helping users make sense of long privacy policies … After the question generation phase, we were left with around 3,00,000 question answer pairs …

An evolutionary approach for personalization of content delivery in e-learning systems based on learner behavior forcing compatibility of learning materials
BCL Christudas, E Kirubakaran… – Telematics and Informatics, 2017 – Elsevier
Skip to main content …

Motivational and Intervention Systems and Monitoring with mHealth Tools
GMT Ahsan – 2017 – epublications.marquette.edu
… 12 3.4.2 Machine Learning Recommender Algorithms … and evidence-based motivational SMS messages to participants. Our solution implements machine learning algorithms that take the participants’ demographic profiles and previous smoking behavior into account …

Relational reasoning in science, medicine, and engineering
D Dumas – Educational Psychology Review, 2017 – Springer
… psychology, the term in silico can be used more broadly to signify not only artificial intelligence work, but also research that utilizes advanced computing techniques to simulate data, or to process data collected from human participants with machine-learning or natural language …

Neural Wikipedian: Generating Textual Summaries from Knowledge Base Triples
P Vougiouklis, H Elsahar, LA Kaffee, C Gravier… – arXiv preprint arXiv …, 2017 – arxiv.org
… Conventional systems based on neural networks when employed on NLG tasks, such as Machine Translation [6] or Question Generation [11] are incapable of learning high quality vector repre- sentation for the infrequent tokens (ie either words or entities) in their training dataset …

An Evaluation of Constituency-based Hyponymy Extraction from Privacy Policies
MC Evans, J Bhatia, S Wadkar… – … Conference (RE), 2017 …, 2017 – ieeexplore.ieee.org
… Snow et al. applied WordNet and machine learning to a newswire corpus to identify lexicoYsyntactic patterns and hyponyms [29]. Their approach includes the six Hearst patterns and resulted in a 54% increase in the number of words over WordNet …

Learner modeling for adaptive scaffolding in a computational thinking-based science learning environment
S Basu, G Biswas, JS Kinnebrew – User Modeling and User-Adapted …, 2017 – Springer
… hypermedia and educational systems, Desmarais and Baker (2012) provide an extensive review of uncertainty-based and machine learning approaches to … This factual knowledge captured in the learner model is then used for automatic multiple-choice question generation …

Factoid Question Answering
A Oromo – etd.aau.edu.et
Page 1. ADDIS ABABA UNIVERSITY SCHOOL OF GRADUATE STUDIES SCHOOL OF INFORMATION SCIENCES Factoid Question Answering For Afaan Oromo A THESIS SUBMITED TO THE SCHOOL OF GRADUTE STUDIES OF …

Curious Cat–Mobile, Context-Aware Conversational Crowdsourcing Knowledge Acquisition
L Bradeško, M Witbrock, J Starc, Z Herga… – ACM Transactions on …, 2017 – dl.acm.org
… It addresses a broad range of as-yet incompletely solved problems from the fields of artificial intelligence, machine learning, natural language … Unlike Curious Cat, which checks answers for validity and has a variety of question generation rules, GOKC has only one rule, is fixed …

A novel X-FEM based fast computational method for crack propagation
Z Cheng, H Wang, PMB Vitanyi, N Chater, M Barzegari… – arxiv.org
… Comments: ICCV 2017. Subjects: Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI); Learning (cs.LG); Machine Learning (stat.ML) … Subjects: Learning (cs.LG); Artificial Intelligence (cs.AI); Machine Learning (stat.ML) …

DDoS attacks in cloud computing: Issues, taxonomy, and future directions
G Somani, MS Gaur, D Sanghi, M Conti… – Computer …, 2017 – Elsevier
Skip to main content …

Design, Architecture and Interface of Protus 2.1 System
A Klašnja-Mili?evi?, B Vesin, M Ivanovi?, Z Budimac… – E-Learning Systems, 2017 – Springer
General tutoring system model, presented in previous chapter, can be used as a skeleton for an implementation of concrete programming tutoring system. This chapter presents details about implementatio.

Inside Out: Detecting Learners’ Confusion to Improve Interactive Digital Learning Environments
A Arguel, L Lockyer, OV Lipp… – Journal of …, 2017 – journals.sagepub.com
Confusion is an emotion that is likely to occur while learning complex information. This emotion can be beneficial to learners in that it can foster engagement,…

ECU convention 2017 research presentations
A Kongsted, L Hestbaek… – Chiropractic & …, 2017 – chiromt.biomedcentral.com
Skip to content Advertisement. BMC. Login My Account Search Menu. Explore journals; Get published; About BMC. Search all BMC articles Search. Chiropractic & Manual Therapies logo Chiropractic & Manual Therapies. Menu. Home; About; Articles; Submission Guidelines …

Learning analytics explained
N Sclater – 2017 – books.google.com
Page 1. |EARNING ANAD(CS EXPLANE Noll Scoter Page 2. Learning Analytics Explained Learning Analytics Explained draws extensively from case studies and interviews with experts in order to discuss emerging applications of the new field of learning analytics …

Intrusion Detection and Prevention System in enhancing Security of Cloud Environment
K Kumar – ijarcet.org
… which consists of Source Checking and Counting module, Multi-Stage Attack Detection module, and Question Generation module [20] … Efficient Intrusion Detection Model Based on Fast Inductive Learning?, Sixth International Conference on Machine Learning and Cybernetics …

Towards the Implementation of an Intelligent Software Agent for the Elderly
AHF Dinevari – 2017 – era.library.ualberta.ca
… DARPA Defense Advanced Research Projects Agency. IE Information Extraction. KR Knowledge Representation. ML Machine Learning. MUC Machine Understanding Conference. NLG Natural Language Generation. NLP Natural Language Processing …

Security challenges in cloud computing: state-of-art
K Bhushan, BB Gupta – International Journal of Big Data …, 2017 – inderscienceonline.com
Page 1. Int. J. Big Data Intelligence, Vol. 4, No. 2, 2017 81 Copyright © 2017 Inderscience Enterprises Ltd. Security challenges in cloud computing: state-of-art Kriti Bhushan and BB Gupta* Department of Computer Engineering …

Asking the right questions about human inquiry
A Coenen, JD Nelson, TM Gureckis – Retrieved from psyarxiv. com/h457v, 2017 – osf.io
… Aside from scientific applications, OED con- cepts are also widely used in machine learning Page 4. 4 THIS PAPER HAS NOT BEEN PEER REVIEWED. PLEASE DO NOT COPY OR CITE WITHOUT AUTHOR’S PERMISSION to develop algorithms that rely on active learn- ing …

Computational Natural Language Inference: Robust and Interpretable Question Answering
RR Sharp – 2017 – search.proquest.com
… In the context of question answering (ie, finding short answers to natural language questions), this inference connects the question with its answer and we learn to approximate this inference with machine learning … learning …

Multimodal Fusion: A Theory And Applications
Y PENG – 2017 – cise.ufl.edu
Page 1. MULTIMODAL FUSION: A THEORY AND APPLICATIONS By YANG PENG A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS …

Autonomous Cars: An Adaptable Feedback Mechanism For Customised Ethics
S Jaiswal – 2017 – dalspace.library.dal.ca
… 63 Figure 15: The flowchart of question generation phase ….. 64 … scenario the sensors of the AV will detect the objects encountered. Next, the detected object will be classified into a category using a machine learning classifier and the priority of the …

SUPR-Qm: A Questionnaire to Measure the Mobile App User Experience.
J Sauro, P Zarolia – Journal of Usability Studies, 2017 – search.ebscohost.com
… Qualitative data from the four free-response questions were coded and summarized by an expert-coding strategy. An analyst read through each of the 104 responses, noting recurring themes to inform future question generation …

Measuring Offensive Speech in Online Political Discourse
R Nithyanand, B Schaffner, P Gill – 7th {USENIX} Workshop on Free and …, 2017 – arxiv.org
… Haloi. Comments: fig added, with minor typo corrections. Subjects: Learning (cs.LG); Machine Learning (stat.ML) … solutions. arXiv:1706.02027 [pdf, ps, other] Title: Question Answering and Question Generation as Dual Tasks …

Serving CS Formative Feedback on Assessments Using Simple and Practical Teacher-Bootstrapped Error Models
K Stephens-Martinez – 2017 – eecs.berkeley.edu
… John DeNero gave me insight into the pedagogy of introductory computer science learning and machine learning … Analysis techniques used in LA include network analysis, information visualization, statistical tests, and machine learning with a foundation in learning theory …

From Discourse Structure to Text Specificity: Studies of Coherence Preferences
JJ Li – 2017 – search.proquest.com
From Discourse Structure to Text Specificity: Studies of Coherence Preferences. Abstract. To successfully communicate through text, a writer needs to organize information into an understandable and well-structured discourse for the targeted audience …

List of Recently Published Quality Research Papers
MN Ansari – Imperial Journal of Interdisciplinary Research, 2017 – imperialjournals.com
… Imperial Journal of Interdisciplinary Research 3.1 (2016). Bhamre, Kalpesh; Patidar, Mr Kailash; Verma, Mr Manoj; .”Survey of Machine Learning Based Text Filtering System for OSN user walls”. Imperial Journal of Interdisciplinary Research 3.1 (2016) …

Determinants of Strategy Selection During Active Inquiry
A Coenen – 2017 – search.proquest.com
… 197. 4.2.3 The role of prior knowledge in question generation . . . . . 206 … theories of optimal experiment design and active learning algorithms from Machine. Learning (Fedorov, 1972; Settles, 2010; KP Murphy, 2001; Tong & Koller, 2001) …

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