Session-based recommendations using item embedding

Asnat Greenstein-Messica, Lior Rokach, Michael Friedmann

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

33 Scopus citations

Abstract

Recent methods for learning vector space representations of words, word embedding, such as GloVe [7] and Word2Vec [5] have succeeded in capturing fine-grained semantic and syntactic regularities. We analyzed the effectiveness of these methods for e-commerce recommender systems by transferring the sequence of items generated by users' browsing journey in an e-commerce website into a sentence of words. We examined the prediction of fine-grained item similarity (such as item most similar to iPhone 6 64GB smart phone) and item analogy (such as iPhone 5 is to iPhone 6 as Samsung S5 is to Samsung S6) using real life users' browsing history of an online European department store. Our results reveal that such methods outperform related models such as singular value decomposition (SVD) with respect to item similarity and analogy tasks across different product categories. Furthermore, these methods produce a highly condensed item vector space representation, item embedding, with behavioral meaning sub-structure. These vectors can be used as features in a variety of recommender system applications. In particular, we used these vectors as features in a neural network based models for anonymous user recommendation based on session's first few clicks. It is found that recurrent neural network that preserves the order of user's clicks outperforms standard neural network, item-To-item similarity and SVD (recall@10 value of 42% based on first three clicks) for this task.

Original languageEnglish
Title of host publicationIUI 2017 - Proceedings of the 22nd International Conference on Intelligent User Interfaces
PublisherAssociation for Computing Machinery
Pages629-633
Number of pages5
ISBN (Electronic)9781450343480
DOIs
StatePublished - 7 Mar 2017
Event22nd International Conference on Intelligent User Interfaces, IUI 2017 - Limassol, Cyprus
Duration: 13 Mar 201716 Mar 2017

Publication series

NameInternational Conference on Intelligent User Interfaces, Proceedings IUI

Conference

Conference22nd International Conference on Intelligent User Interfaces, IUI 2017
Country/TerritoryCyprus
CityLimassol
Period13/03/1716/03/17

Keywords

  • Deep learning
  • E-commerce
  • Glove
  • Item embedding
  • Recurrent neural network
  • Session-based recommender system
  • Word embedding
  • Word2vec

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction

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