Automatic Generation of MCQs Using Information Extraction

Name: Automatic Generation of MCQs Using Information Extraction
Brand: LAP Lambert Academic Publishing
SKU: 9783659901638
Price: 25118 HUF
Availability: InStock

Szerző: Naveed Afzal

Nyelv:

Kötés: Puha kötésű

Kiadó: LAP Lambert Academic Publishing

Elérhetőség: Beszállítói készleten

Küldés 5-8 napon belül

25 118 Ft

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

Információk a könyvről

Szerző

Naveed Afzal

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2016

oldal

272

EAN

9783659901638

Enbook ID

13510934

Kiadó

LAP Lambert Academic Publishing

Súly

421

Méretek

150 x 220 x 16

Teljes leírás

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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