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Multi-level Deep Learning based e-Commerce Product Categorization
2018
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
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In the E-Commerce Text Classification Challenge, we combine machine learning, deep learning, and natural language processing to propose a multi-level and multi-class deep learning tree method. ...
E-commerce product categorization is an important topic, and its quality directly affects subsequent search, recommendations and related personalized services. ...
ACKNOWLEDGMENTS #is work was partially supported by the SIGIR eCom`18 Project "Taxonomy Classification for eCommerce-scale Product Catalogs" and by Rakuten Institute of Technology Boston (RIT-Boston). ...
dblp:conf/sigir/YuSLLZ18
fatcat:kninapgvefgjbgy5g4zz3r7ady
Categorizing Multi-Label Product Questionnaires through SVM Based Click stream
2020
International journal of recent technology and engineering
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Traditional supervised approaches to E-Commerce QC are not possible due to the high volume of traffic and high cost for manual annotation in E-Commerce search engines. ...
Despite this, search queries about the product usually vary depending on what is vague, and introduce new products over time, seasonal trends and narrow. ...
Its two-level structures are both sentence representation and deep word representation; it has the ability to learn both. ...
doi:10.35940/ijrte.f8012.059120
fatcat:ie2lqob52rh7nefuv6r6jcfnxe
Applications of Fusion Techniques in E-Commerce Environments: A Literature Review
2022
Sensors
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, based on the wide variety of challenges faced by e-commerce. ...
For categorizing the solutions, a novel 4-fold categorization approach is introduced including product-related, economy-related, business-related, and consumer-related solutions, followed by relevant subcategorizations ...
Finally, in the e-commerce product categorization solution proposed by Yu et al. ...
doi:10.3390/s22113998
pmid:35684619
pmcid:PMC9182987
fatcat:63ztbmzfuvdk3hjagtss5iihey
Don't Classify, Translate: Multi-Level E-Commerce Product Categorization Via Machine Translation
[article]
2018
arXiv
pre-print
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E-commerce platforms categorize their products into a multi-level taxonomy tree with thousands of leaf categories. ...
Conventional methods for product categorization are typically based on machine learning classification algorithms. ...
Conclusion & Future Work Product categorization is an important problem for e-commerce companies. ...
arXiv:1812.05774v1
fatcat:ki545ztt4rcynhnzg4gyg3pwz4
Large-scale Multi-class and Hierarchical Product Categorization for an E-commerce Giant
2016
International Conference on Computational Linguistics
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In order to organize the large number of products listed in e-commerce sites, each product is usually assigned to one of the multi-level categories in the taxonomy tree. ...
We have trained our models for around 150 million products with a taxonomy tree with at most 5 levels that contains 28,338 leaf categories. ...
In this paper we propose a large-scale classification method for e-commerce products to classify them into thousands of multi-level categories. ...
dblp:conf/coling/CevahirM16
fatcat:qdoecskru5eitl42r7p5ldxpa4
APRF-Net: Attentive Pseudo-Relevance Feedback Network for Query Categorization
[article]
2021
arXiv
pre-print
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Query categorization is an essential part of query intent understanding in e-commerce search. ...
A common query categorization task is to select the relevant fine-grained product categories in a product taxonomy. ...
e-commerce. ...
arXiv:2104.11384v2
fatcat:hdsijcybg5aklaunkwvr2suiou
Multi-label classification of promotions in digital leaflets using textual and visual information
[article]
2020
arXiv
pre-print
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Product descriptions in e-commerce platforms contain detailed and valuable information about retailers assortment. ...
In particular, coding promotions within digital leaflets are of great interest in e-commerce as they capture the attention of consumers by showing regular promotions for different products. ...
We believe that the automated product coding in digital leaflets is at an early research stage but yet it is a very interesting approach in the future of e-commerce. ...
arXiv:2010.03331v1
fatcat:azypui2qw5asfeoes33zrxsepq
Is a picture worth a thousand words? A Deep Multi-Modal Fusion Architecture for Product Classification in e-commerce
[article]
2016
arXiv
pre-print
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Classifying products into categories precisely and efficiently is a major challenge in modern e-commerce. ...
In this paper, we propose a decision level fusion approach for multi-modal product classification using text and image inputs. ...
Thus, precisely categorizing items emerges as a significant issue in e-commerce domains. ...
arXiv:1611.09534v1
fatcat:fzrqysiswrekhhmhf26rwhjmsy
Everyone Likes Shopping! Multi-class Product Categorization for e-Commerce
2015
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
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One of the biggest challenges in e-Commerce is that providers like Amazon, e-Bay, Google, Yahoo! ...
We conducted an empirical evaluation on 445, 408 product titles and used a rich product taxonomy of 319 categories organized into 6 levels. ...
Such process will both alleviate human labor and further improve product categorization consistency in e-Commerce websites. ...
doi:10.3115/v1/n15-1147
dblp:conf/naacl/Kozareva15
fatcat:nvyxkiq75ff33lhhzp5opdzinu
A Visual Technique to Analyze Flow of Information in a Machine Learning System
2018
IS&T International Symposium on Electronic Imaging Science and Technology
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2019 pre-print arXiv:1908.00754v1 fatcat:qnl2kw7lsvc2jdkxaozxrscniu
The proposed concept is illustrated with the example of categorization of millions of products in the e-commerce domain - a multi-class hierarchical classification problem. ...
Machine learning (ML) algorithms and machine learning based software systems implicitly or explicitly involve complex flow of information between various entities such as training data, feature space, ...
Application Scenario The product catalog of an e-commerce company typically contains millions of products that need to be placed into categories structured as multi-level hierarchies (such as electronics ...
doi:10.2352/issn.2470-1173.2018.01.vda-380
fatcat:d7hnzemv7vcfpeeyku65wuvd2e
Content-based E-commerce Image Classification Research
2020
IEEE Access
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This paper uses content-based and deep learning methods to classify e-commerce images. Content-based image classification has been widely studied. ...
[24] proposed an image classification method based on deep learning feature coding model. ...
doi:10.1109/access.2020.3018877
fatcat:tjn2pvdamzbotndmzsot3fjaje
User Response Prediction in Online Advertising
[article]
2021
arXiv
pre-print
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We propose a taxonomy to categorize state-of-the-art user response prediction methods, primarily focus on the current progress of machine learning methods used in different online platforms. ...
prosperity of online campaigns is a challenge in online marketing and is usually evaluated by user response through different metrics, such as clicks on advertisement (ad) creatives, subscriptions to products ...
In the context of e-commerce websites, [5] suggested multi-modal ensemble learning to consider texts and images of posts as different modalities. ...
arXiv:2101.02342v2
fatcat:clgefamcd5fmbeg5ephizy3zqu
JointMap: Joint Query Intent Understanding For Modeling Intent Hierarchies in E-commerce Search
[article]
2020
arXiv
pre-print
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In the e-commerce domain, recent work in query understanding focuses on the query to product-category mapping. ...
In this paper, we introduce Joint Query Intent Understanding (JointMap), a deep learning model to simultaneously learn two different high-level user intent tasks: 1) identifying a query's commercial vs ...
CONCLUSIONS AND FUTURE WORK We introduced JointMap, a deep learning model designed for jointly learning two high-level intent tasks on e-commerce search data. ...
arXiv:2005.13783v2
fatcat:7epqkxseszcr3e4gc6dr2bzmo4
Markdowns in E-Commerce Fresh Retail: A Counterfactual Prediction and Multi-Period Optimization Approach
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2105.08313v1 fatcat:2hknfs7fabdallzz6sjhtb5yzq
Secondly, we propose a multi-period dynamic pricing algorithm to maximize the overall profit of a perishable product over its finite selling horizon. ...
Experimental results show the advantages of our pricing algorithm, and the proposed framework has been successfully deployed to the well-known e-commerce fresh retail scenario - Freshippo. ...
In particular, we denote categorical feature as ∈ {0, 1} , and assume there are three level categories. ...
arXiv:2105.08313v2
fatcat:atxzob6c7veb5a6725o7h3lt54
Text Classification for Predicting Multi-level Product Categories
[article]
2021
arXiv
pre-print
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In addition, we observe that using bilingual product titles is generally beneficial, and neural network-based models perform significantly better than SVM and XGBoost models. ...
We perform a comprehensive comparison of six different text classification models to establish a strong baseline for this task, which involves testing both traditional and recent machine learning methods ...
The interest in e-commerce has only increased with the COVID-19 pandemic, which resulted in the proliferation of e-commerce companies [4] . ...
arXiv:2109.01084v1
fatcat:agofx4ijpfdkvcbumobyowythm
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