Question answering using machine learning



a new reading comprehension dataset, consisting of questions posed by crowdworkers on a set o f Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage.
Question answering using a large text database: A machine learning approach
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In this paper, we present a machine learning approach to question answering. The task is answering factual questions, where the answers are to be found in documents in a large text database. We trained our system on 398 questions from the Remedia corpus, as well as 38

A machine learning approach for indonesian question answering system.
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Our research is to investigate a machine learning approach in order to build an Indonesian Question Answering System. Based on our experiments result on the question classification task, we choose to use SVM as the machine learning algorithm. Similar with ordinary QA

Question classification using Naïve Bayes machine learning approach
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Question classification is very important for question answering system. The features include words, bigrams, and trigrams, as well as the parts of speech in each sentence. Many approaches to question classification have been proposed and have achieved reasonable

A machine learning approach for factoid question answering
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This paper presents a factoid Question Answering system that is fully based on machine learning . Our system achieves similar results to a state-of-theart QA system with answer extraction rules developed by a human expert. Our approach avoids human intervention and

Distributed nlp and machine learning for question answering grid
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We regard question answering as Semantic Grid application in which the answering process is best expressed as a distributed computing task and show, how the workflow control of this distributed QA task can be learned automatically. Since the control protocol contains

Machine learning based question classification methods in the question answering systems
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The Question Answering Systems (QASs) use method of information retrieval and Information extraction to retrieves documents that contain special answers to the question . One of the existence problems is finding the desired information from this very high variety

Concept recognition, information retrieval, and machine learning in genomics question -answering.
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TREC Genomics 2006 presented a genomics question -answering challenge with questions on twenty-seven topics, and a corpus of 16 259 full-text biomedical journal articles from which to derive answers. Questions were formulated from actual information needs of

Web-based Arabic question answering system using machine learning approach
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Question Answering (QA) systems are complex software capable of answering a question in natural language. The source of information for these systems is a given corpus or, as assumed here, the Web. To generate the exact answer, these systems carry out several

Arabic question classification using machine learning approaches
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Question Classification is a very important component in question answering system. In this paper, we present a machine learning comparison study for classifying Arabic questions. We have used two taxonomies: Arabic taxonomy and Li Roth taxonomy. We have conducted

Supervised machine learning techniques for question answering
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In this paper, we discuss three components of our question answering system, focusing on our application of machine learning techniques. In particular, we describe our use of Support Vector Machines (SVMs) for the selection of sentences that contain answers to queries. Our

Towards Automatic Analyses of Police Interviews Machine Learning of Question Types
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One of the indicators for the quality of a police interrogation is the type of questions the interviewer asks. Can machine learning be used to automatically tell what type of question is meant by the utterance of the interviewer Using a multidimensional annotation scheme for

Measuring issue salience: Using supervised machine learning to generate data from free responses to the most important problem question
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Future political communication research will depend on measuring issue-salience in massive data sets largely consisting of unstructured text. We examine a set of supervised machine – learning approaches that can categorize short segments of unstructured text data

Machine Learning Question Bank
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GB CN 2018 13.127.246.217 4. What do you mean by a well posed learning problem Explain the important features that are required to well define a learning problem. 5. Explain the inductive biased hypothesis space and unbiased learner 6. What are the basic design issues and approaches to

Machine Learning Based Question Classification
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Question classification is of crucial importance for question answering. In question classification, the accuracy of ML algorithms was found to significantly outperform other approaches. The two key issues in classification with a ML-based approach are classifier

Machine Learning Approaches for Bengali Automated Question Detection System
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Question detection is the initial tasks of question answering system. Question detection, the first step of QA system has been done applying SVM, Logistic Regression, K-Neighbor classifier, Multilayer Perceptron and LSTM. We achieved best performance for SVM with

QUEZARD: Question Wizard using Machine Learning and Artificial Intelligence
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Presenting highly comprehensive and advanced system which works as an assistant of students throughout their process of learning and teacher while process of teaching. The system mainly consists of two platforms: an Android application and machine learning

Machine Learning Approach for Question Answering in Information Retrieval
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ABSTRACT CQA (Community Question Answering) is a major challenge nowadays due to the popularity and advantages of CQA archives over the web. This paper deals with the methods to solve lexical gap problem in question retrieval and providing multiple domain

Automatic Multiple Choice Question Generator by Using Machine Learning
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Abstract English reading comprehension is one of the most required skill for people whose native language is not English. One example is when you study in an English spoken country, you have to read many literatures supporting the course in English language

Machine Learning of SPARQL Templates for Question Answering over LinkedSpending (Discussion Paper)
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We present a Question Answering system aimed to answer natural language questions over open RDF spending data provided by LinkedSpeding. We propose an original machine – learning approach to learn generalized SPARQL templates from an existing training set of