Automatic Generation of MCQs Using Information Extraction

Name: Automatic Generation of MCQs Using Information Extraction
Brand: LAP Lambert Academic Publishing
SKU: 9783659901638
Price: 1473 CZK
Availability: InStock

Autor: Naveed Afzal

Jazyk:

Vazba: Brožovaná

Vydavatel: LAP Lambert Academic Publishing

Dostupnost: Skladem u dodavatele

Odesíláme za 5-8 dnů

1 473 Kč

Multiple Choice Tests (MCTs) are a popular form of assessment and are quite frequently used by many...

Informace o knize

Autor

Naveed Afzal

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2016

Stránek

272

EAN

9783659901638

Enbook ID

13510934

Vydavatel

LAP Lambert Academic Publishing

Hmotnost

421

Rozměry

150 x 220 x 16

Kompletní popis

Multiple Choice Tests (MCTs) are a popular form of assessment and are quite frequently used by many e-Learning applications as they are well adapted to assessing factual, conceptual and procedural information. In this research work, we present an alternative to the lengthy and time-consuming activity of developing MCTs by proposing a Natural Language Processing (NLP) based approach that relies on semantic relations extracted using Information Extraction to automatically generate MCTs. Information Extraction (IE) is an NLP field used to recognise the most important entities present in a text, and the relations between those concepts, regardless of their surface realisations. In IE, text is processed at a semantic level that allows the partial representation of the meaning of a sentence to be produced. In this work, we present two unsupervised RE approaches (surface-based and dependency-based). The aim of both approaches is to identify the most important semantic relations in a document without assigning explicit labels to them in order to ensure broad coverage, unrestricted to predefined types of relations.

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Automatic Generation of MCQs Using Information Extraction

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