Design and Development of a Fashion Oriented Personalized Search Engine

Abstract

Finding the desired product in the e-commerce sector in the fastest and easiest way plays a vital role in customer satisfaction and revenue growth. Some interactive search engines have already been proposed in the literature and allow for text or visual queries. Nevertheless, these studies focus on finding items aesthetically similar to the query without considering the query personalization aspects. Query personalization allows that user preferences are provided as a user profile separately from the query and dynamically decide how this profile will affect the query results. In this study, a personalized search engine is proposed, which is fed with the product data of the e-commerce site trendyol.com operating in the fashion-oriented retailing sector. More specifically, a search engine has been developed to recognize and help online shoppers find what they are looking for and discover a broader and more relevant range of products in the trendyol.com catalog. The index, search, and data collection infrastructures and a brand-based user-segmented product listing algorithm have been designed and implemented to realize the search engine. As the outcome of the study, a fashion-oriented and personalized site search has been enabled thar successfully reveals products that have never been thought of before by directly associating the products the customers want. The results show that personalizing the search queries increase the odds of success. With the development of the personalized search engine, it is expected that Trendyol’s revenues will grow in a short time through users visiting the site.

Keywords

• Information Retrieval
• Prediction
• Query Personalization
• Search Engine

References

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