Papers by Tolga Uslu
LTV: Labeled Topic Vector (C18-2)
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| Challenge: | Using nnDDC, we generate labeled topic classifications based on the Dewey Decimal Classification (DDC) Unlike related approaches, we use classifiers to define the dimensions of CISS, which are directly labeles by the underlying target class. |
| Approach: | They propose a website and API that generates labeled topic classifications based on the Dewey Decimal Classification (DDC) they propose nnDDC, a largely language-independent natural network-based classifier for DDC, which is language-dependent . |
| Outcome: | The proposed model is language-independent and performs well in 40 languages. |
FastSense: An Efficient Word Sense Disambiguation Classifier (L18-1)
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| Challenge: | Word Sense Disambiguation (WSD) is a task that is often overlooked by NLP pipelines because of its complexity and complexity. |
| Approach: | They propose a neural network-based tool for word sense disambiguation called fastSense. |
| Outcome: | The proposed tool can process huge amounts of data quickly and surpasses state-of-the-art tools in terms of F-measure. |