This work shows the early stages of the development of a collaborative-filtering-inspired adaptive system to streamline the ordering process at restaurants that use electronic me...
The 3rd International Workshop on News Recommendation and Analytics (INRA 2015) is held in conjunction with RecSys 2015 Conference in Vienna, Austria. This paper presents a brief ...
We propose an alternative way to efficiently exploit rating data for collaborative filtering with Factorization Machines (FMs). Our approach partitions user-item matrix into ‘...
An essential characteristic in many e-commerce settings is that website visitors can have very specific short-term shopping goals when they browse the site. Relying solely on lon...
With the increasing accessibility of transactional data in venture finance, venture capital firms (VCs) face great challenges in developing quantitative tools to identify new in...
In the midst of vast amounts of available fashion items, consumers today require more efficient recommendation services. A system that sorts out items that form a stylish ensemble...
Personalised news recommender systems traditionally rely on content ingested from a select set of publishers and ask users to indicate their interests from a predefined list of t...
Experts are important for providing reliable and authoritative information and opinion, as well as for improving online reviews and services. While considerable previous research ...
Recommender systems (RSs) enhance e-commerce sales by recommending relevant products to their customers. RSs aim at implementing the firm's web-based marketing strategy to in...
In this paper, we evaluate the accuracy of personality-based recommendations using a real-world data set from Amazon.com. We automatically infer the personality traits, needs, and...