Here is presented a platform for automatic composition of inductive learning systems using ontologies called CAMLET, based on knowledge modeling and ontologies engineering technique. CAMLET constructs an inductive learning system with better competence to a given data set, using process and object ontologies. Afterwards, CAMLET instantiates and re nes a constructed system based on the following...

We study a novel task, Video Question-Answer Generation (VQAG), for challenging Question Answering (Video QA) task in multimedia. Due to expensive data annotation costs, many widely used, large-scale QA datasets such as Video-QA, MSVD-QA and MSRVTT-QA are automatically annotated using Caption (CapQG) which inputs captions instead of the video itself. As neither fully represent video, nor they a...

We propose a query-based generative model for solving both tasks of question generation (QG) and question answering (QA). The model follows the classic encoderdecoder framework. The encoder takes a passage and a query as input then performs query understanding by matching the query with the passage from multiple perspectives. The decoder is an attention-based Long Short Term Memory (LSTM) model...

Current massively open online courses (MOOCs) are providing several technical challenges for educators. One of these challenges is automated generation of questions, along with the solutions, in order to deal with a large number of students. Geometry is an important part of the high school curriculum. Hence, in this paper, we have focused on the high school geometry domain. We have proposed a f...

the aim of this paper is to present four strategies to increase the accuracy and speed of optimization of truss structures under the constraint of structural system failure probability (ssfp). in the first strategy based on the probability rules, a criterion is defined to avoid producing many correlated paths and obtain more accurate upper bound of ssfp. in the second strategy, the force method...

Recently, researchers from multiple disciplines have been showing their common interest in automatic question generation for educational purposes. In this paper, we review the state of the art of approaches to developing educational applications of question generation. We conclude that although a great variety of techniques on automatic question generation exists, just a small amount of educati...

Online knowledge sharing sites have recently exploded in popularity, and have began to play an important role in online information seeking. Unfortunately, many factors that influence the effectiveness of the information exchange in these communities are not well understood. This paper is an attempt to fill this gap by exploring the dynamics of information sharing in such sites that is, identif...

Question generation from text is a Natural Language Generation task of vital importance for self-directed learning. Learners have access to learning materials from a wide variety of sources, and these materials are not often accompanied by questions to help guide learning. Prior question generation techniques have focused primarily on generating factoid questions, which are often not the most p...

Giving an adequate general definition of the input to natural language generation (NLG), and hence to NLG itself, is a notoriously difficult problem, practically, theoretically and even methodologically. In this paper, we describe our recent experiences of implementing an NLG component of a larger question-answering system, and trying to understand and resolve some of these problems in this con...