• Corpus ID: 212609374

AN INTELLIGENT APPAREL RECOMMENDATION SYSTEM FOR ONLINE SHOPPING USING STYLE CLASSIFICATION

@inproceedings{Perkinian2015ANIA,
  title={AN INTELLIGENT APPAREL RECOMMENDATION SYSTEM FOR ONLINE SHOPPING USING STYLE CLASSIFICATION},
  author={C. Perkinian and P. Vikkraman},
  year={2015}
}
Managing and selecting proper clothes has long been a challenging problem especially in today’s world where people are always in hurry and hence most of the time they end up choosing to wear the same dressing styles or the same piece of clothes. In addition, the people tend to stick with one or two dressing styles and buy new clothes that are very similar to the ones they already have. This usually results in a huge waste of time and money. In this paper, we propose a new intelligent apparel… 
Apparel-based deep learning system design for apparel style recommendation
TLDR
The results indicate that adding the proposed ATTRIBUTE data that captures the deep features of clothes design does improve the model performances, and the new concept of apparel recommendation based on style meanings is technically applicable.
Recommendation Framework Combining User Interests with Fashion Trends in Apparel Online Shopping
  • Ok, Lee, Kim
  • Computer Science
    Applied Sciences
  • 2019
TLDR
To overcome the rating sparsity problem of online apparel datasets, implicit ratings from user log data and predicted ratings for item clusters are derived and combined with a network constructed by an item click trend, which serves as a personalized recommendation through a random walk.
AN INTELLIGENT APPAREL RECOMMENDATION SYSTEM FOR ONLINE SHOPPING USING STYLE CLASSIFICATION
TLDR
A new intelligent apparel recommendation system for online shopping using style classification that makes recommendations of clothes based on past and present sales data on different styles and is validated using opinion from questionnaires and experts.

References

SHOWING 1-10 OF 29 REFERENCES
One-to-one recommendation system in apparel online shopping
TLDR
An apparel online shopping site with a fashion adviser existing on the Internet, who has detailed knowledge about the fashions in the real shop, selects and coordinates the clothes of the customer's preference and makes recommendations of other clothes based on past sales data.
An Intelligent On-line Recommendation System in B2C Apparel e-Commerce
TLDR
This paper proposes an intelligent apparel on-line recommendation platform that is supported by a framework which provides the desired personalization and reports the design and analysis for this system.
Apparel Classification with Style
We introduce a complete pipeline for recognizing and classifying people's clothing in natural scenes. This has several interesting applications, including e-commerce, event and activity recognition,
Collaborative filtering recommender systems
TLDR
This study presents an overview of the field of recommender systems with current generation of recommendation methods and examines comprehensively CF systems with its algorithms.
Trust-Aware Recommender Systems
TLDR
This chapter gives an overview of state-of-theart recommender systems with a focus on trust-awareRecommender systems and describes the ways that trust information can help to improve the quality of the recommendations.
Predicting occupation via human clothing and contexts
TLDR
The preliminary study shows the human occupation is reasonably predictable using the proposed clothing features and possible context and this description of human clothing is proved to be more effective than traditional methods.
Intelligent feature selection and classification techniques for intrusion detection in networks: a survey
TLDR
A survey on intelligent techniques for feature selection and classification for intrusion detection in networks based on intelligent software agents, neural networks, genetic algorithms, neuro-genetic algorithms, fuzzy techniques, rough sets, and particle swarm intelligence is proposed.
Clothes search in consumer photos via color matching and attribute learning
TLDR
A novel framework is presented to tackle automatic clothes search in consumer photos by leveraging low- level features (e.g., color) and high-level features (attributes) of clothes by leveraging the bag-of-visual-words model.
Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set
In this paper, we address a practical problem of cross-scenario clothing retrieval - given a daily human photo captured in general environment, e.g., on street, finding similar clothing in online
...
...