Voting with Generative AI for German Compound Splitting in E-commerce Search

Compound words are a grammatical structure that allows forming new words by composing existing words. For e-commerce search in German, it is essential to split these compounds into meaningful parts because item titles often use the joint form while search queries are often split. We propose a method for German compound splitting leveraging a large language model (LLM) with a voting mechanism and a hyperparameter search for automatically optimizing prompt and parameter combinations. Our evaluation of the proposed method on human-created gold standard data for e-commerce shows that it outperforms existing methods for compound splitting in this domain.

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Published
2024-10-20
DOI
https://doi.org/10.1145/3627673.3679074
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
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article

Voting with Generative AI for German Compound Splitting in E-commerce Search

Ümit Yılmaz, Kilian Merkelbach, Daniel T. Stein, Hasan Oezkan
Natural Language Processing Techniques
article

Voting with Generative AI for German Compound Splitting in E-commerce Search

Ümit Yılmaz, Kilian Merkelbach, Daniel T. Stein, Hasan Oezkan
article en

Abstract

Compound words are a grammatical structure that allows forming new words by composing existing words. For e-commerce search in German, it is essential to split these compounds into meaningful parts because item titles often use the joint form while search queries are often split. We propose a method for German compound splitting leveraging a large language model (LLM) with a voting mechanism and a hyperparameter search for automatically optimizing prompt and parameter combinations. Our evaluation of the proposed method on human-created gold standard data for e-commerce shows that it outperforms existing methods for compound splitting in this domain.

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Natural Language Processing Techniques
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