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Special Issue: Fashion Recommender Systems 

Lecture Notes in Social Networks (LNSN) - Springer Journal Volume

Call for papers

Online Fashion retailers have increased in popularity over the last decade, making it possible for customers to explore hundreds of thousands of products without the need to visit multiple stores or stand in long queues for checkout. There exists a number of hurdles that customers face with current online shopping solutions. For example, they often feel overwhelmed with the large selection of the assortment and brands. In addition, there is still a lack of effective suggestions capable of satisfying their style preferences. Determining the right size and fit during the purchase journey is one of the major factors not only impacting customers purchase decision, but also their satisfaction from e-commerce fashion platforms. Most importantly, the impact of social networks and influence that fashion influencers have on the choices people make for shopping is undeniable. 

The Fashion Recommender Systems book aims to present a state of the art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. This is not a college textbook. However, it can be used as a reference text for advanced courses on Cross-domain information retrieval, fashion recommendation algorithms, social network mining and analysis, computer vision and deep learning applications, among numerous others. Through this edited volume, we intend to create a venue to bring together researchers and practitioners from different disciplines, to share, exchange, learn, and develop preliminary results, new concepts, ideas, principles, and methodologies, aiming to advance the area of fashion recommendation.

Read more about the LNSN volume here: 

Suggested topics for submissions are (but not limited to):


Important dates


Authors Submission Due: February 10, 2020

Reviews Submission and Authors Notifications: March 15, 2020
Authors Revisions Due: March 31st, 2020


Submission guidelines


All papers should follow the manuscript preparation guidelines for the Springer Lecture Notes in Social Network Analysis submissions, see Instructions for Authors section at:

The authors are requested to submit their manuscripts via the online submission manuscript system, available at

Should there be any further inquiries, please address them to the coordinating guest editor for the special issue at: [log in to unmask]

Best wishes, 

Nima Dokoohaki

LNSN volume editor​

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