The 3A Personalized, Contextual and Relation-based Recommender System

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We present algorithms for the (1+epsilon)-approximate version of the closest vector problem for certain norms. The currently fastest algorithm (Dadush and Kun 2016) for general norms in dimension n has running time of 2(O(n)) (1/epsilon)(n) . We improve th ...

The ever-growing amount of online information calls for Personalization. Among the various personalization systems, recommenders have become increasingly popular in recent years. Recommenders typically use collaborative filtering to suggest the most releva ...

Recommenders are central in many applications today. The most effective recommendation schemes, such as those based on collaborative filtering (CF), exploit similarities between user profiles to make recommendations, but potentially expose private data. Fe ...

Drones are rapidly becoming an affordable and often faster solution for parcel delivery than terrestrial vehicles. Existing transportation drones and software infrastructures are mostly designed by logistics companies for trained users and dedicated infras ...

Capturing students' behavioral patterns through analysis of sequential interaction logs, is an important task in educational data mining to enable more effective personalized support during the learning process. This study aims at discovery and temporal an ...

Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...

At the core of the contribution of this dissertation there is an augmented reality (AR) environment, StaticAR, that supports the process of learning the fundamentals of statics in vocational classrooms, particularly in carpentry ones. Vocational apprentice ...

Networks are data structures that are fundamental for capturing and analyzing complex interactions between objects. While they have been used for decades to solve problems in virtually all scientific fields, their usage for data analysis in real-world prac ...

In applications that involve interactive curve and surface modeling, the intuitive manipulation of shapes is crucial. For instance, user interaction is facilitated if a geometrical object can be manipulated through control points that interpolate the shape ...

The origins of modern recommender systems date back to the early 1990s when they were mainly applied experimentally to personal email and information filtering. Today, 30 years later, personalized recommendations are ubiquitous and research in this highly ...

The goal of this tutorial is to provide the WSDM community with recent advances on the assessment and mitigation of data and algorithmic bias in recommender systems. We first introduce conceptual foundations, by presenting the state of the art and describi ...

Teleoperation of an agricultural robotic system requires effective and efficient human-robot interaction. This paper investigates the usability of different interaction modes for agricultural robot teleoperation. Specifically, we examined the overall influ ...

Online education platforms play an increasingly important role in mediating the success of individuals' careers. Therefore, while building overlying content recommendation services, it becomes essential to guarantee that learners are provided with equal re ...

In the last decade, online social networks have enabled people to interact in many ways with each other and with content. The digital traces of such actions reveal people's preferences towards online content such as news or products. These traces often res ...

The 3A Personalized, Contextual and Relation-based Recommender System

Chat with Graph Search

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