Multilingual Search with Subword TF-IDF

• URL: http://arxiv.org/abs/2209.14281v2
• Date: Thu, 29 Sep 2022 02:39:46 GMT
• Title: Multilingual Search with Subword TF-IDF
• Authors: Artit Wangperawong
• Abstract summary: subword TF-IDF (STF-IDF) can offer higher accuracy without suchs. XQuAD evaluation demonstrates the advantages of STF-IDF: superior information retrieval accuracy of 85.4% for English.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Multilingual search can be achieved with subword tokenization. The accuracy of traditional TF-IDF approaches depend on manually curated tokenization, stop words and stemming rules, whereas subword TF-IDF (STF-IDF) can offer higher accuracy without such heuristics. Moreover, multilingual support can be incorporated inherently as part of the subword tokenization model training. XQuAD evaluation demonstrates the advantages of STF-IDF: superior information retrieval accuracy of 85.4% for English and over 80% for 10 other languages without any heuristics-based preprocessing. The software to reproduce these results are open-sourced as a part of Text2Text: https://github.com/artitw/text2text

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