Using Word Embeddings for Ontology Enrichment

İzzet Pembeci

doi:https://doi.org/10.18201/ijisae.58806

Article Details

Using Word Embeddings for Ontology Enrichment

Authors:

İzzet Pembeci

Publisher:

İsmail SARITAŞ

Journal:

International Journal of Intelligent Systems and Applications in Engineering 2016 Vol.4 Issue 3, pp.49-56

Document Type:

Article

Publication Date:

10/2016

Document Language:

Turkish

Document ID (Org No.):

2000817556

Frequency:

Quarterly

eISSN:

2147-6799

DOI:

https://doi.org/10.18201/ijisae.58806

Abstract:

 

Word embeddings, distributed word representations in a reduced linear space, show a lot of promise for accomplishing Natural Language Processing (NLP) tasks in an unsupervised manner. In this study, we investigate if the success of word2vec, a Neural Networks based word embeddings algorithm, can be replicated in an aggluginative language like Turkish. Turkish is more challenging than languages like English for complex NLP tasks because of her rich morphology. We picked ontology enrichment, again a relatively harder NLP task, as our test application. Firstly, we show how ontological relations can be extracted automaticaly from Turkish Wikipedia to construct a gold standard. Then by running experiments we show that the word vector representations produced by word2vec are useful to detect ontological relations encoded in Wikipedia. We propose a simple but yet effective weakly supervised ontology enrichment algorithm where for a given word a few know ontologically related concepts coupled with similarity scores computed via word2vec models can result in discovery of other related concepts. We argue how our algorithm can be improved and augmented to make it a viable component of an ontoloy learning and population framework.

Article Details

Using Word Embeddings for Ontology Enrichment

Authors: İzzet Pembeci

Publisher: İsmail SARITAŞ

Journal: International Journal of Intelligent Systems and Applications in Engineering 2016 Vol.4 Issue 3, pp.49-56

Document Type: Article

Publication Date: 10/2016

Document Language: Turkish

Document ID (Org No.): 2000817556

Frequency: Quarterly

eISSN: 2147-6799

DOI: https://doi.org/10.18201/ijisae.58806

Issues

Authors:

İzzet Pembeci

Publisher:

İsmail SARITAŞ

Journal:

International Journal of Intelligent Systems and Applications in Engineering 2016 Vol.4 Issue 3, pp.49-56

Document Type:

Article

Publication Date:

10/2016

Document Language:

Turkish

Document ID (Org No.):

2000817556

Frequency:

Quarterly

eISSN:

2147-6799

DOI:

https://doi.org/10.18201/ijisae.58806