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Register a new userEvaluation of Taxonomy Enrichment on Diachronic WordNet Versions
تقييم التخصيب التصنيفي في إصدارات WordNet DIACHRONIC
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تطبق الغالبية العظمى من الأساليب الحالية لتخصيص التصنيفات في تطبق Adgeddings Word لأنها أثبتت تجميع السياقات (بمعنى واسع) المستخرجة من النصوص التي تكفي إرفاق الكلمات الأيتام بالتصنيف.من ناحية أخرى، وبصرف النظر عن كونها الموارد الكبيرة المعجمية واللاللالية، فإن التصنيفات هي هياكل رسم بيانية.يمكن أن يكون الجمع بين تدمير Word مع هيكل الرسم البياني للتصنيف موضع التنبؤ بالتنبؤ بالعلاقات التصنيفية.في هذه الورقة، نقارن العديد من النهج لإرفاق كلمات جديدة بالتصنيف الموجود القائمة على تمثيلات الرسم البياني مع تلك التي تعتمد على ASTTEXT AGEDDINGS.نختبر جميع الأساليب على مجموعات البيانات الروسية والإنجليزية، ولكن يمكن تطبيقها أيضا على الكلمات واللغات الأخرى.
The vast majority of the existing approaches for taxonomy enrichment apply word embeddings as they have proven to accumulate contexts (in a broad sense) extracted from texts which are sufficient for attaching orphan words to the taxonomy. On the other hand, apart from being large lexical and semantic resources, taxonomies are graph structures. Combining word embeddings with graph structure of taxonomy could be of use for predicting taxonomic relations. In this paper we compare several approaches for attaching new words to the existing taxonomy which are based on the graph representations with the one that relies on fastText embeddings. We test all methods on Russian and English datasets, but they could be also applied to other wordnets and languages.
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