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Learning-oriented Question Recommendation

Name: Learning-oriented Question Recommendation
Brand: Sudwestdeutscher Verlag Fur Hochschulschriften AG
SKU: 9783838134154
Price: 64.04 EUR
Availability: InStock

Автор: Andreea Hilda Kosorus

Език:

Корици: С меки корици

Издател: Sudwestdeutscher Verlag Fur Hochschulschriften AG

Наличност: Външен склад

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The information overload in the past two decades has enabled question-answering (QA) systems to accu...

Информация за книгата

Автор

Andreea Hilda Kosorus

Език

Английски език

Корици

Книга - С меки корици

Издадена

2014

страници

196

EAN

9783838134154

ISBN

383813415X

Enbook ID

06987815

Издател

Sudwestdeutscher Verlag Fur Hochschulschriften AG

Теглоt

295

Размери

152 x 229 x 11

Пълно описание

The information overload in the past two decades has enabled question-answering (QA) systems to accumulate large amounts of textual fragments that reflect human knowledge. Therefore, such systems have become not just a source for information retrieval, but also a means towards a unique learning experience. Meanwhile, the success of recommender systems has motivated research on deploying recommendation techniques also in educational environments to facilitate access to a wide spectrum of information. However, the adopted methods were rather traditional, generally applicable to any recommendation need. Current conceptions about learning assume learners as active agents and not passive recipients or simple recorders of information. Therefore, the sequence in which knowledge is assimilated is of high importance. Recently developed recommendation techniques for search engine queries try to leverage the order in which users navigate through them. However, these are not suitable for QA systems. In this work we address the challenge of learning-oriented question recommendation by adopting variable length Markov chains and Bloom's learning taxonomy.

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