Work

Keli̇me Temsi̇lleri̇ İçi̇n Test Performansini Geli̇şti̇rmeye Yöneli̇k Eşdi̇zi̇mli̇li̇k Ağirliklarinin Seçi̇mi̇

Year: 2018

Type: article

Abstract: This study revisits the problem of maximizing the performance of mathematical word representations for a given task. It is aimed to improve performance in analogy and similarity tasks by suggesting innovative weights instead of the counting weights used conventionally in counting-based methods of generating word representations (adding the statistics of word co-occurrences to the account). The language of study was selected as Turkish. The root structures of Turkish words were managed during the compilation of corpus such that each word having a suffix was considered as a new word. The performance of the proposed co-occurrence weights are analyzed with respect to the varying parameter and the results are presented within the paper.

Source: Uludağ University Journal of The Faculty of Engineering

DOI: 10.17482/uumfd.318615

Authors: Aykut Koç, Veysel Yücesoy

Institution: Aselsan (Turkey)

Language: Turkish

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W2796102736

FWCI:

Cites: 17

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Related to: 10