Keyphrase extraction is the task of automatically selecting a small set of phrases that best
describe a given free text document. Supervised keyphrase extraction requires large …

These years much effort has been devoted to improving the accuracy or relevance of the
recommendation system. Diversity, a crucial factor which measures the dissimilarity among …

The determinantal point process (DPP) is an elegant probabilistic model of repulsion with
applications in various machine learning tasks including summarization and search …

Feed recommendation systems, which recommend a sequence of items for users to browse
and interact with, have gained significant popularity in practical applications. In feed …

In traditional recommender system literature, diversity is often seen as the opposite of
similarity, and typically defined as the distance between identified topics, categories or word …

Nowadays, in information systems such as web search engines and databases, diversity is
becoming increasingly essential and getting more and more attention for improving users' …

We address the problem of image collection summarization by learning mixtures of
submodular functions. We argue that submodularity is very natural to this problem, and we …

The classical K Shortest Paths (KSP) problem, which identifies the k shortest paths in a
directed graph, plays an important role in many application domains, such as providing …

With the ever-increasing popularity of microservice architecture, a considerable number of
enterprises or organizations have encapsulated their complex business services into …

Data generation and labeling are usually an expensive part of learning for robotics. While
active learning methods are commonly used to tackle the former problem, preference-based …