Related papers: Some like it hot - visual guidance for preference …
Preference elicitation plays a central role in interactive recommender systems. Most preference elicitation approaches use either item queries that ask users to select preferred items from a slate, or attribute queries that ask them to…
In this work, we explore the features that are used by humans and by convolutional neural networks (ConvNets) to classify faces. We use Guided Backpropagation (GB) to visualize the facial features that influence the output of a ConvNet the…
People in the Internet era have to cope with the information overload, striving to find what they are interested in, and usually face this situation by following a limited number of sources or friends that best match their interests. A…
Every day, a significant number of users visit the internet for different needs. The owners of a website generate profits from the user interaction with the contents or items of the website. A robust recommendation system can increase user…
Face recognition has been widely accepted as a means of identification in applications ranging from border control to security in the banking sector. Surprisingly, while widely accepted, we still lack the understanding of uniqueness or…
Personalizing image tags is a relatively new and growing area of research, and in order to advance this research community, we must review and challenge the de-facto standard of defining tag importance. We believe that for greater progress…
Collaborative filtering or recommender systems use a database about user preferences to predict additional topics or products a new user might like. In this paper we describe several algorithms designed for this task, including techniques…
Recommender systems attempts to identify and recommend the most preferable item (product-service) to an individual user. These systems predict user interest in items based on related items, users, and the interactions between items and…
Online comments play a crucial role in shaping public sentiment and opinion dynamics on social media. However, evaluating their popularity remains challenging, not only because it depends on linguistic quality, originality, and emotional…
Billions of photos are uploaded to the web daily through various types of social networks. Some of these images receive millions of views and become popular, whereas others remain completely unnoticed. This raises the problem of predicting…
Personalized video highlight detection aims to shorten a long video to interesting moments according to a user's preference, which has recently raised the community's attention. Current methods regard the user's history as holistic…
User preference profiling is an important task in modern online social networks (OSN). With the proliferation of image-centric social platforms, such as Pinterest, visual contents have become one of the most informative data streams for…
Predicting the future popularity of online content is highly important in many applications. Preferential attachment phenomena is encountered in scale free networks.Under it's influece popular items get more popular thereby resulting in…
Different from shopping in physical stores, where people have the opportunity to closely check a product (e.g., touching the surface of a T-shirt or smelling the scent of perfume) before making a purchase decision, online shoppers rely…
For a given identity in a face dataset, there are certain iconic images which are more representative of the subject than others. In this paper, we explore the problem of computing the iconicity of a face. The premise of the proposed…
Online dating platforms have fundamentally transformed the formation of romantic relationships, with millions of users worldwide relying on algorithmic matching systems to find compatible partners. However, current recommendation systems in…
Motivated by online dating platforms, we study the problem of selecting which subset of profiles to display to each user in each period. Users observe the profiles set by the platform, decide which of them to like, and a match occurs if and…
Neural collaborative filtering is the state of art field in the recommender systems area; it provides some models that obtain accurate predictions and recommendations. These models are regression-based, and they just return rating…
Aging or gender variation can affect the face recognition performance dramatically. While most of the face recognition studies are focused on the variation of pose, illumination and expression, it is important to consider the influence of…
Computational social scientists often harness the Web as a "societal observatory" where data about human social behavior is collected. This data enables novel investigations of psychological, anthropological and sociological research…