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Improving Relevance Quality in Product Search using High-Precision Query-Product Semantic Similarity
Ensuring relevance quality in product search is a critical task as it impacts the customer’s ability to find intended products in the short-term as well as the general perception and trust of the e-commerce system in the long term.
Spelling Correction using Phonetics in E-commerce Search
In E-commerce search, spelling correction plays an important role to find desired products for customers in processing user-typed search queries.
Towards Scalability and Extensibility of Query Reformulation Modeling in E-commerce Search
Notably, employing the proposed solution in search ranking resulted in 0. 14% and 0. 29% increase in overall revenue in Japanese and Hindi cases, respectively, and a 0. 08\% incremental gain in the English case compared to the legacy implementation; while in search Ads matching led to a 0. 36% increase in Ads revenue in the Japanese case.
Incentivized Bandit Learning with Self-Reinforcing User Preferences
In this paper, we investigate a new multi-armed bandit (MAB) online learning model that considers real-world phenomena in many recommender systems: (i) the learning agent cannot pull the arms by itself and thus has to offer rewards to users to incentivize arm-pulling indirectly; and (ii) if users with specific arm preferences are well rewarded, they induce a "self-reinforcing" effect in the sense that they will attract more users of similar arm preferences.
