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Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy
2022 Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining  
However, these models lack (i) a hierarchical query representation, (ii) a mechanism to detect and capture inter-entity relationships within a query, and (iii) a query composition method specific to e-commerce  ...  We evaluate the performance of our model on real data collected from popular e-commerce sites.  ...  This is empirical evidence that ANTHEM's spatially-aware query hyperboloids form better search space for E-commerce queries.  ... 
doi:10.1145/3488560.3498456 fatcat:5skmjm7x6vfeppjo7x5kamo4em

Session-aware Information Embedding for E-commerce Product Recommendation

Chen Wu, Ming Yan
2017 Proceedings of the 2017 ACM on Conference on Information and Knowledge Management - CIKM '17  
We conduct quantitative experiments on a recently published dataset from an e-commerce company.  ...  Based on the learnt session representation, we further propose a list-wise ranking model to generate the recommendation result for each anonymous user session.  ...  Given a collection of anonymous user session logs in e-commerce website ( i.e., user clicks, views and purchases), and a collection of presented products, the goal of the session-aware recommendation is  ... 
doi:10.1145/3132847.3133163 dblp:conf/cikm/WuY17 fatcat:xz6y6vjs3nektmnsswxkjg7i54

Query Tracking for E-commerce Conversational Search: A Machine Comprehension Perspective [article]

Yunlun Yang, Yu Gong, Xi Chen
2018 arXiv   pre-print
Further more we build a novel E-commerce query tracking dataset from an operational E-commerce Search Engine, and experimental results on this dataset suggest that our proposed model outperforms several  ...  However, comparing with the natural language understanding in traditional task-oriented dialog which focuses on slot filling and tracking, the query understanding in E-commerce conversational search is  ...  INTRODUCTION Searching is often the first step for a user when he want to seek specific products on an E-commerce website.  ... 
arXiv:1810.03274v1 fatcat:idk6c4ey6zhqraxmonclqzw4oy

Dynamic Intention-Aware Recommendation System [article]

Shuai Zhang, Lina Yao
2017 arXiv   pre-print
In this paper, we propose a dynamic intention-aware recommender system to better facilitate users to find desirable products and services.  ...  Compare to prior work, our proposal possesses the following advantages: (1) it takes user intentions and demands into account through intention mining techniques.  ...  To model the dynamic intentions, we mainly investigate two techniques: HMM and RNN. HMM is an e cient dynamic tool for modelling sequential data.  ... 
arXiv:1703.03112v2 fatcat:af3jq4emcna6heoyujwxwqdmgu

Interpretable Attribute-based Action-aware Bandits for Within-Session Personalization in E-commerce

Xu Liu, Congzhe Su, Amey Barapatre, Xiaoting Zhao, Diane Hu, Chu-Cheng Hsieh, Jingrui He
2021 IEEE Data Engineering Bulletin  
As such, it is increasingly important for e-commerce ranking systems to quickly learn a buyer's fine-grained preferences and re-rank items based on their most recent activity within the session.  ...  modeling preferences at the product category level).  ...  from a production e-commerce ranking system.  ... 
dblp:journals/debu/0016SBZHHH21 fatcat:z3zlis547fe6nf3kxsyv6vfwpe

Social media intention mining for sustainable information systems: categories, taxonomy, datasets and challenges

Ayesha Rashid, Muhammad Shoaib Farooq, Adnan Abid, Tariq Umer, Ali Kashif Bashir, Yousaf Bin Zikria
2021 Complex & Intelligent Systems  
Search engines are a major source to infer users' past searching activities to predict their intention, facilitating the vendors and manufacturers to present their products to the user in a promising manner  ...  The analysis reveals that there exist eight prominent categories of intention. Furthermore, a taxonomy of the approaches and techniques used for intention mining have been discussed in this article.  ...  To predict dynamic query and generic search intents, search for a product on the e-commerce portal, and explore search intentions on touch enable digital devices. Qian et al.  ... 
doi:10.1007/s40747-021-00342-9 fatcat:ak3y4ao2sbffjd5b3rbttidvjy

Attentive Sequential Models of Latent Intent for Next Item Recommendation

Md Mehrab Tanjim, Congzhe Su, Ethan Benjamin, Diane Hu, Liangjie Hong, Julian McAuley
2020 Proceedings of The Web Conference 2020  
Results from our experiments show that our model can capture the dynamics of user behavior and preferences, leading to state-of-the-art performance across datasets from two major e-commerce platforms,  ...  Our model first learns item similarities from users' interaction histories via a self-attention layer, then uses a Temporal Convolutional Network layer to obtain a latent representation of the user's intent  ...  Although BPR-MF can learn static user preference, it cannot capture sequential dynamics. Hence, all deep sequential models which are capable of learning such dynamics, outperform BPR-MF.  ... 
doi:10.1145/3366423.3380002 dblp:conf/www/TanjimSBHHM20 fatcat:ywr7ktpgcrblhnri46mtbfr7xi

PSAC: Context-based Purchase Prediction Framework via User's Sequential Actions

Wei-Cheng Chen, Chih-Yu Wang, Su-Chen Lin, Alex Ou, Tzu-Chiang Liou
2019 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval  
We find that query should play an important role as well as it is the main entry point for users when arriving e-commerce website.  ...  Experimental results confirm that queries serve as a critical matter in perceiving a user's purchasing intention.  ...  ACKNOWLEDGMENTS This work was supported by the Ministry of and Technology under Grant MOST 105-2221-E-001-003-MY3 and the Academia Sinica under Grand Challenge Seed Project AS-GC-108-01.  ... 
dblp:conf/sigir/ChenWLOL19 fatcat:hmzytmzstff53idw6uzwnhgl3i

Relation-Aware Graph Convolutional Networks for Agent-Initiated Social E-Commerce Recommendation

Fengli Xu, Jianxun Lian, Zhenyu Han, Yong Li, Yujian Xu, Xing Xie
2019 Proceedings of the 28th ACM International Conference on Information and Knowledge Management - CIKM '19  
To address these problems, we propose RecoGCN, which stands for a RElation-aware CO-attentive GCN model, to effectively aggregate heterogeneous features in a HIN.  ...  Recent years have witnessed a phenomenal success of agent-initiated social e-commerce models, which encourage users to become selling agents to promote items through their social connections.  ...  To conclude, the visualization shows that RecoGCN can effectively learned semantic-aware representations for social e-commerce network.  ... 
doi:10.1145/3357384.3357924 dblp:conf/cikm/XuLHLX019 fatcat:wgznfbekajeg5kezix2dgjeecm

Report on the SIGIR 2019 Workshop on eCommerce (ECOM19) [article]

Jon Degenhardt, Surya Kallumadi, Utkarsh Porwal, Andrew Trotman
2019 arXiv   pre-print
The purpose of the workshop was to serve as a platform for publication and discussion of Information Retrieval and NLP research and their applications in the domain of eCommerce.  ...  A second goal was to run a data challenge on real-world eCommerce data.  ...  Thanks also to the panelists, and participants for their contribution to the workshop.  ... 
arXiv:1912.12282v1 fatcat:6cwvvxjnnbfy5czmhl76oakg2q

E-Commerce Customers Behavior Research Using Cohort Analysis: A Case Study of COVID-19

Solomiia Fedushko, Taras Ustyianovych
2022 Journal of Open Innovation: Technology, Market and Complexity  
Key e-business aspects from a customer point of view are analyzed and augment the user-experience understanding to strengthen customers' relationships in e-commerce.  ...  Obtained insights on e-commerce customers' awareness and loyalty levels show the likeliness of a user to make a purchase or interact with the platform.  ...  Yun J.J and others developed a quadruplehelix model to understand its dynamics in various areas [63] .  ... 
doi:10.3390/joitmc8010012 fatcat:rr44uhoaqzcyxnjjkwvzwghyli

Sequence-Aware Recommender Systems [article]

Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach
2018 arXiv   pre-print
Academic research in the field is historically often based on the matrix completion problem formulation, where for each user-item-pair only one interaction (e.g., a rating) is considered.  ...  And, a number of recent works have shown that this information can be used to build richer individual user models and to discover additional behavioral patterns that can be leveraged in the recommendation  ...  In this situation, a sequence-aware recommender system can be based on a combination of longterm and short-term interest models, e.g., in e-commerce settings or for app recommendation [9, 40, 56, 91]  ... 
arXiv:1802.08452v1 fatcat:edjtdc6355cx3bbq2nkelogiqy

CrEOS: Identifying Critical Events in Online Sessions

Meghanath Macha, Shankar Venkitachalam, Deepak Pai
2020 Companion Proceedings of the Web Conference 2020  
We validate CrEOS on click-stream data of a large US based e-commerce firm, compare it with single variable LSTM and discuss the insights derived from the critical event identification considering a series  ...  In this work, we propose CrEOS contributing to the extant literature in the deployment of deep learning techniques to model online consumer behaviour.  ...  For an e-commerce website, the events in E i k i usually comprise of product home page, cart addition, review page etc.  ... 
doi:10.1145/3366424.3382185 dblp:conf/www/MachaVP20 fatcat:zyczc62jwbfnbmcn7krwqa6nny

Fantastic Embeddings and How to Align Them: Zero-Shot Inference in a Multi-Shop Scenario [article]

Federico Bianchi, Jacopo Tagliabue, Bingqing Yu, Luca Bigon, Ciro Greco
2020 arXiv   pre-print
We then turn to the harder task of using learned embeddings across shops: if products from different shops live in the same vector space, user intent - as represented by regions in this space - can then  ...  This paper addresses the challenge of leveraging multiple embedding spaces for multi-shop personalization, proving that zero-shot inference is possible by transferring shopping intent from one website  ...  Special thanks to Andrea Polonioli for his support.  ... 
arXiv:2007.14906v1 fatcat:j3dd2v3rdrbx3btt6vixe4w2ou

Sequence-Aware Recommender Systems

Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach
2018 ACM Computing Surveys  
Academic research in the field is historically often based on the matrix completion problem formulation, where for each user-item-pair only one interaction (e.g., a rating) is considered.  ...  And, a number of recent works have shown that this information can be used to build richer individual user models and to discover additional behavioral patterns that can be leveraged in the recommendation  ...  in e-commerce.  ... 
doi:10.1145/3190616 fatcat:p3wuhyx2yvgfzo5k6lugjuxobu
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