Prashnottar: A Hindi Question Answering System

ABSTRAC

Quran Ontology: Review On Recent Development And Open Research Issues

Quran is the holy book of Muslims that contains the commandment of words of Allah. Quran provides instructions and guidance to humankind in achieving happiness in life in the world and the hereafter. As a holy book, Quran contains rich knowledge and scientific facts. However, humans have difficulty in understanding the Quran content. It is caused by the fact that the meaning of the searched message content depends on the interpretation. Ontology able to store the knowledge representation of Holy Quran. This paper studies recent ontology on Holy Quran research. We investigate the current trends and technology being applied. This investigation cover on several aspects, such as outcomes of previous studies, language which used on ontology development, coverage area of Quran ontology, datasets, tools to perform ontology development ontology population techniques, approaches used to integrate the knowledge of Quran and other resources into ontology, ontology testing techniques, and limitations on previous research. This review has identified four major issues involved in Quran ontology, i.e. availability of Quran ontology in various translation, ontology resources, automated process of Meronymy relationship extraction, and Instances Classification. The review of existing studies will allow future researchers to have a broad and useful background knowledge on primary and essential aspects of this research field

Question Answering System : A Review On Question Analysis, Document Processing, And Answer Extraction Techniques

Question Answering System could automatically provide an answer to a question posed by human in natural languages. This system consists of question analysis, document processing, and answer extraction module. Question Analysis module has task to translate query into a form that can be processed by document processing module. Document processing is a technique for identifying candidate documents, containing answer relevant to the user query. Furthermore, answer extraction module receives the set of passages from document processing module, then determine the best answers to user. Challenge to optimize Question Answering framework is to increase the performance of all modules in the framework. The performance of all modules that has not been optimized has led to the less accurate answer from question answering systems. Based on this issues, the objective of this study is to review the current state of question analysis, document processing, and answer extraction techniques. Result from this study reveals the potential research issues, namely morphology analysis, question classification, and term weighting algorithm for question classification

Provision of better VLE learner support with a Question Answering System

The focus of this research is based on the provision of user support to students using electronic means of communication to aid their learning. Digital age brought anytime anywhere access of learning resources to students. Most academic institutions and also companies use Virtual Learning Environments to provide their learners with learning material. All learners using the VLE have access to the same material and help despite their existing knowledge and interests. This work uses the information in the learning materials of Virtual Learning Environments to answer questions and provide student help by a Question Answering System. The aim of this investigation is to research if a satisfactory combination of Question Answering, Information Retrieval and Automatic Summarisation techniques within a VLE will help/support the student better than existing systems (full text search engines)