The Language Program aim to convert the vast unstructured data of Rakuten into structured one. The focus lies primarily with catalog data to acquire the following benefits:
-Better product search in Rakuten Ichiba
-Effective filtering for products
-Quicker understanding of demand of products for superior product matching and recommendation
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- The Language Program aim to convert the vast unstructured data of Rakuten into structured one. The focus lies primarily with catalog data to acquire the following benefits:
Create structured product data using AI
The language program is another vertical of Rakuten Institute of Technology. This group comprises of AI researchers who are specialized in natural language processing techniques. The goal of this group is to convert the vast unstructured data of Rakuten into structured one. The focus lies with catalog data primarily. Benefits of structured catalog data are numerous, ranging from better product search in Rakuten Ichiba, effective filtering for products, quicker understanding of demand of products, to superior product matching and recommendation.
Key techniques used for converting unstructured data to structured ones include attribute extraction for must-have attributes, attribute normalization for critical attributes to ensure consistency, key-word extraction, and others to name a few. We also have a dedicated Machine Translation team on a mission to help Rakuten strengthen its global presence and lower language barriers by developing language translation solutions for Rakuten’s portfolio businesses.
Automated product catalog
Rakuten is one of the largest e-commerce platforms in Japan with more than 300 million products. The clean, structured item data that captures the key features is one of the foundational technologies to innovate the shopping experience. It leads to the purchase decision-making for the customers, such as size and color information for fashion and spec information for electronics. Once we have the data, we believe it is possible to make a much better discovery and search experience based on AI. However, the challenging with creating such structured data is that it is very costly and requires manual processing.
In the Language program, we strive to develop a fully automated AI catalog where all the necessary technologies for structures such as item categorization, feature extraction, query, and customer behavior understanding and normalizations are conducted by automated AI with small inputs from annotations.
In addition, Rakuten aims to become one of the largest communication platforms with Rakuten Mobile and Viber. Rakuten's dedicated Machine Translation team is supporting the vision by focusing on eliminating language barriers and facilitating communications for Rakuten customers worldwide.
Rakuten's dedicated Machine Translation team is on a mission to help Rakuten strengthen its global presence and lower language barriers by developing language translation solutions for Rakuten’s portfolio businesses. Rakuten Translate helps translate content of Rakuten’s global services, such as video subtitles, e-commerce product descriptions, and travel booking information, into multiple languages using deep learning technology. The Rakuten Translate team was awarded a special prize at the Nikkei Deep Learning Business Awards in October 2019 in recognition of its excellence in generating new businesses and social impact using deep learning.
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Corpus Augmentation for Tagging Japanese Product Attribute Values in Low-resource SettingsSIGIR eCom
A Large-Scale Challenging Japanese Dataset for Aspect-based Sentiment AnalysisSIGIR eCom
Extreme Multi-Label Classification with Label Masking for Product Attribute Value ExtractionECNLP2022