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Shop Weatherly – A Weather based Smart E-Commerce System Using CNN
2021
Revista GEINTEC
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In this paper, we proposed a novel idea by using Convolutional Neural Network Algorithm of deep learning for developing an e-commerce platform that is unique in a way that it recommends clothes according ...
People go shopping when the weather gets changed. For travelers, there is no such E-commerce platform that can recommend clothes according to any city weather. ...
Sallar Khan for his continuous support in the paradigm of research implementation methods. ...
doi:10.47059/revistageintec.v11i4.2318
fatcat:ksqyhs346zcndmlcjv5nskozy4
Towards Automated Website Classification by Deep Learning
[article]
2021
arXiv
pre-print
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Essentially, we tackle a text classification task: an algorithm must learn to infer whether an Italian enterprise performs e-commerce from the textual content of its website. ...
Empirical evidence shows that our proposal outperforms all the alternative Machine Learning solutions already tested in Istat for the same task. ...
informationsensing mobile devices, search engines and software logs, sensor networks, e-commerce and stock market transactions, large-scale scientific experiments, and so on. ...
arXiv:1910.09991v2
fatcat:khotuyt64jei7i4betrts7gvb4
AI-Empowered Persuasive Video Generation: A Survey
[article]
2021
arXiv
pre-print
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In order to produce such contents to support a large applications (e.g., e-commerce), the field of artificial intelligence (AI)-empowered persuasive video generation (AIPVG) has gained traction in recent ...
Promotional videos are rapidly becoming a popular medium for persuading people to change their behaviours in many settings (e.g., online shopping, social enterprise initiatives). ...
Thus, using item IDs in e-commerce
platforms to label VMs might introduce such noises.
7.1.2 Noise Resistant Deep Metric Learning. For large scale VM datasets, label noises are inevitable. ...
arXiv:2112.09401v1
fatcat:t5bsqo6shbcoleryphaawewevy
Smart Fashion: A Review of AI Applications in the Fashion Apparel Industry
[article]
2021
arXiv
pre-print
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The implementation of machine learning, computer vision, and artificial intelligence (AI) in fashion applications is opening lots of new opportunities for this industry. ...
For each task, a time chart is provided to analyze the progress through the years. ...
Shop, ASOS fashion e-commerce 42 Hidayati [320] Graph, Auxiliary visual words, BoVW, AP clustering Celebrities, Body shape, Style 43 Ok [447] User-based CF, Graph-based random walk, ~7% R@10 Fashion ...
arXiv:2111.00905v2
fatcat:6n6d62lntjfu5pxmjzgi4mpv6i
Study on the limitations of Stacking Technique for Bandwidth Improvement of Microstrip Patch Antennas
2021
American journal of science & engineering
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E-commerce has reduced human effort by reducing
physical work and saving time of the seller and buyer both.The main advantage of E-commerce is that the user can browse
online shops and ...
the background study, E-commerce has to Place stress on developing a method enabling
be made feasible for a large spectrum of you to shine brighter ...
doi:10.15864/ajse.2305
fatcat:mr7d7o3rsfe4npbo6apifsi4yy
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources
[article]
2020
arXiv
pre-print
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We first introduce the basic concepts of HG and discuss the unique challenges brought by the heterogeneity for HG embedding in comparison with homogeneous graph representation learning; and then we systemically ...
Heterogeneous graphs (HGs) also known as heterogeneous information networks have become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn representations in a lower-dimension ...
Usually, large-scale heterogeneous objects and interactions, such as users, items, and shops, are involved in an e-commerce platform. ...
arXiv:2011.14867v1
fatcat:phfoxj7qsrfshfednomeok7pau
Fashion Meets Computer Vision: A Survey
[article]
2021
arXiv
pre-print
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Fashion, mainly conveyed by vision, has thus attracted much attention from computer vision researchers in recent years. ...
For each task, the benchmark datasets and the evaluation protocols are summarized. Furthermore, we highlight promising directions for future research. ...
scale, rich and diverse in content in order to
collect as many as possible beauty and personal care items
e-commerce websites
DeepFashion2 [38]
2019
491,000
a versatile benchmark of four tasks ...
arXiv:2003.13988v2
fatcat:ajzvyn4ck5gqxk5ht5u3mrdmba
Product-Aware Answer Generation in E-Commerce Question-Answering
[article]
2019
arXiv
pre-print
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In e-commerce portals, generating answers for product-related questions has become a crucial task. ...
Conducted on a large-scale real-world e-commerce dataset, our extensive experiments verify the effectiveness of each module in our proposed model. ...
ACKNOWLEDGMENTS We would like to thank the anonymous reviewers for their constructive comments. ...
arXiv:1901.07696v2
fatcat:lskfjm4jtzdhzo6y2mggc7cify
Social media intention mining for sustainable information systems: categories, taxonomy, datasets and challenges
2021
Complex & Intelligent Systems
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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 ...
Similarly, six important types of data sets used for this purpose have also been discussed in this work. ...
In [30] , an encoder-decoder neural architecture was proposed to mine users browse or purchase intents and behaviors from large scale datasets of e-commerce. ...
doi:10.1007/s40747-021-00342-9
fatcat:ak3y4ao2sbffjd5b3rbttidvjy
How to derive causal insights for digital commerce in china? a research commentary on computational social science methods
2019
Electronic Commerce Research and Applications
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How to derive causal insights for digital commerce in China? A research commentary on computational social science methods. (2019). ...
Context: 121 articles in e-commerce
literature
Data: Small data set from targeted
literature
Large-scale lit survey yielding detailed analysis and
classification
33 search strings for content, resulting ...
What can be learned for this for development of mobile agent-based e-commerce? ...
doi:10.1016/j.elerap.2019.100837
fatcat:segj5fu3evdqdjveyd54w7cbwq
Explainable Recommendation: A Survey and New Perspectives
[article]
2020
arXiv
pre-print
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In recent years, a large number of explainable recommendation approaches -- especially model-based methods -- have been proposed and applied in real-world systems. ...
In this survey, we provide a comprehensive review for the explainable recommendation research. ...
Any opinions, findings and conclusions expressed in this material are those of the authors and do not necessarily reflect those of the sponsors. ...
arXiv:1804.11192v10
fatcat:scsd3htz65brbiae35zd3nixe4
The Emerging Trends of Multi-Label Learning
[article]
2020
arXiv
pre-print
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2020 pre-print arXiv:2011.11197v1 fatcat:zexkygo5tzf4pi7p2ig45kjdeuOther Versions
Exabytes of data are generated daily by humans, leading to the growing need for new efforts in dealing with the grand challenges for multi-label learning brought by big data. ...
Besides these, there are tremendous efforts on how to harvest the strong learning capability of deep learning to better capture the label dependencies in multi-label learning, which is the key for deep ...
To accelerate it on large-scale e-commerce data, they also propose a heterogeneous graph-based variant that runs on the user-item bipartite graph directly. ...
arXiv:2011.11197v2
fatcat:hu6w4vgnwbcqrinrdfytmmjbjm
Fashion Recommendation Systems, Models and Methods: A Review
2021
Informatics
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On e-commerce platforms, where numerous choices are available, an efficient recommendation system is required to sort, order, and efficiently convey relevant product content or information to users. ...
This paper will help researchers, academics, and practitioners who are interested in machine learning, computer vision, and fashion retailing to understand the characteristics of the different fashion ...
Acknowledgments: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. ...
doi:10.3390/informatics8030049
fatcat:2djpad5hwraqnb6v24pg4b4a5m
Demystifying Core Ranking in Pinterest Image Search
[article]
2018
arXiv
pre-print
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In this work, we share how we practically design and deploy various ranking pipelines into Pinterest image search ecosystem. ...
Pinterest Image Search Engine helps hundreds of millions of users discover interesting content everyday. This motivates us to improve the image search quality by evolving our ranking techniques. ...
Thanks very much to the entire teams of engineers in search feature, search quality and search infra, especially to Chao Tan, Randall Keller, Wenchang Hu, Matthew Fong, Laksh Bhasin, Ying Huang, Zheng ...
arXiv:1803.09799v1
fatcat:jwrua7dkcjg7dcbaddq3xziyru
Deep Learning in Information Security
[article]
2018
arXiv
pre-print
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Deep Learning is a sub-field of machine learning, which uses models that are composed of multiple layers. ...
If DL-methods succeed to solve problems on a data type in one domain, they most likely will also succeed on similar data from another domain. ...
Very Deep Convolutional Networks for Large-Scale Image Recognition. ArXiv
e-prints, 2014.
[137] Suphannee Sivakorn, Iasonas Polakis, and Angelos D. Keromytis. ...
arXiv:1809.04332v1
fatcat:xfb7lgrkw5cirdl3qvmg3ssnbi
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