An essential component of building a successful crowdsourcing market is effective task matching, which matches a given task to the right crowdworkers. In order to provide highquality task matching, crowdsourcing systems rely on past task-solving activities of crowdworkers. However, the average number of past activities of crowdworkers in most crowdsourcing systems is very small. We call the wor...

User groups on photo sharing websites, such as Flickr, are self-organized communities to share photos and conversations with similar interest and have gained massive popularity. However, the huge volume of groups brings troubles for users to decide which group to choose. Further, directly applying collaborative filtering techniques to group recommendation will suffer from cold start problem sin...

An optimization framework for three-dimensional conformal radiation therapy is presented. In this type of therapy, beams of radiation are applied to a patient from different directions, where the aperture through which the beam is delivered from each direction is chosen to match the shape of the tumor, as viewed from that direction. Given a set of equispaced beam angles, a mixed-integer linear ...

Collaborative filtering is one of the most common approaches in many current recommender systems. However, historical data and customer profiles, necessary for this approach, are not always available. Similarly, new products are constantly launched to the market lacking historical information. We propose a new method to deal with these “cold start” scenarios, designing price-estimation function...

We propose an algorithm that combines supervised and unsupervised methods to ensemble multiple systems for two popular Knowledge Base Population (KBP) tasks, Cold Start Slot Filling (CSSF) and Tri-lingual Entity Discovery and Linking (TEDL). We demonstrate that it outperforms the best system for both tasks in the 2015 competition, several ensembling baselines, as well as a state-of-the-art stac...

To develop a recommender system, the collaborative filtering is the best known approach, which considers the ratings of users who have similar rating profiles or rating patterns. Consistently, it is able to compute the similarity of users when there are enough ratings expressed by users. Therefore, a major challenge of the collaborative filtering approach can be how to make recommendations for ...

Today, full-texts of scientific articles are often stored in different locations than the used datasets. Dataset registries aim at a closer integration by making datasets citable but authors typically refer to datasets using inconsistent abbreviations and heterogeneous metadata (e.g. title, publication year). It is thus hard to reproduce research results, to access datasets for further analysis...

Data-driven systems such as the Hint Factory have been successful at providing student guidance by extracting procedural hints from prior user data. However, when only small amounts of data are available, it may be unable to do so. We present a novel hint-selection algorithm for coherent derivational domains, such as probability, which addresses this problem by searching a frontier of viable, p...

Cold atomic gases placed in optical lattice potentials offer a unique tool to study simple tight binding models. Both the standard cases known from the condensed matter theory as well as novel situations may be addressed. Cold atoms setting allows for a precise control of parameters of the systems discussed, stimulating new questions and problems. The attempts to treat disorder in a controlled ...

Web-based catch-up TV services allow users to watch programs at their favoured time and device and are revolutionizing the existing TV watching habits. With the increasing offer and demand for catch-up TV, it has become evident that there is a need for personalised recommendations that will help users to pick programs of interest from a large collection of available content. In order to mitigat...