相关论文: Face to Purchase: Predicting Consumer Choices with…

This dissertation examines three distinct big data analytics problems related to the social aspects of consumers' choices. The main goal of this line of research is to help two sided platform firms to target their marketing policies given…

Network embedding, which aims to learn low-dimensional representations of nodes, has been used for various graph related tasks including visualization, link prediction and node classification. Most existing embedding methods rely solely on…

Facial recognition has become a widely used method for authentication and identification, with applications for secure access and locating missing persons. Its success is largely attributed to deep learning, which leverages large datasets…

This study investigates the impact of dynamic user profile embedding on personalized context-aware experiences in social networks. A comparative analysis of multilingual and English transformer models was performed on a dataset of over…

Humans have come to rely on machines for reducing excessive information to manageable representations. But this reliance can be abused -- strategic machines might craft representations that manipulate their users. How can a user make good…

Recent studies have shown that information disclosed on social network sites (such as Facebook) can be used to predict personal characteristics with surprisingly high accuracy. In this paper we examine a method to give online users…

Accurately modeling user preferences is vital not only for improving recommendation performance but also for enhancing transparency in recommender systems. Conventional user profiling methods, such as averaging item embeddings, often…

Face detection is a long-standing challenge in the field of computer vision, with the ultimate goal being to accurately localize human faces in an unconstrained environment. There are significant technical hurdles in making these systems…

Identifying key product features that influence consumer preferences is essential in the fashion industry. In this study, we introduce a robust methodology to ascertain the most impactful features in fashion product images, utilizing past…

Embedding methods have achieved success in face recognition by comparing facial features in a latent semantic space. However, in a fully unconstrained face setting, the facial features learned by the embedding model could be ambiguous or…

Predicting future successful designs and corresponding market opportunity is a fundamental goal of product design firms. There is accordingly a long history of quantitative approaches that aim to capture diverse consumer preferences, and…

Product recommendation systems have been instrumental in online commerce since the early days. Their development is expanded further with the help of big data and advanced deep learning methods, where consumer profiling is central. The…

While several approaches to face emotion recognition task are proposed in literature, none of them reports on power consumption nor inference time required to run the system in an embedded environment. Without adequate knowledge about these…

Facial appearance matters in social networks. Individuals frequently make trait judgments from facial clues. Although these face-based impressions lack the evidence to determine validity, they are of vital importance, because they may…

We employ the face recognition technology developed in house at face.com to a well accepted benchmark and show that without any tuning we are able to considerably surpass state of the art results. Much of the improvement is concentrated in…

Modern recommender systems model people and items by discovering or `teasing apart' the underlying dimensions that encode the properties of items and users' preferences toward them. Critically, such dimensions are uncovered based on user…

With increasing importance of e-commerce, many websites have emerged where users can express their opinions about products, such as movies, books, songs, etc. Such interactions can be modeled as bipartite graphs where the weight of the…

As online content becomes ever more visual, the demand for searching by visual queries grows correspondingly stronger. Shop The Look is an online shopping discovery service at Pinterest, leveraging visual search to enable users to find and…

The continuous growth of electronic commerce has stimulated great interest in studying online consumer behavior. Given the significant growth in online shopping, better understanding of customers allows better marketing strategies to be…

Recommendations are commonly used to modify user's natural behavior, for example, increasing product sales or the time spent on a website. This results in a gap between the ultimate business objective and the classical setup where…