Zobrazeno 1 - 10
of 95
pro vyhledávání: '"Alstrup, Stephen"'
Semantic hashing represents documents as compact binary vectors (hash codes) and allows both efficient and effective similarity search in large-scale information retrieval. The state of the art has primarily focused on learning hash codes that improv
Externí odkaz:
http://arxiv.org/abs/2103.14460
Semantic Hashing is a popular family of methods for efficient similarity search in large-scale datasets. In Semantic Hashing, documents are encoded as short binary vectors (i.e., hash codes), such that semantic similarity can be efficiently computed
Externí odkaz:
http://arxiv.org/abs/2007.00380
Autor:
Hansen, Christian, Hansen, Casper, Simonsen, Jakob Grue, Larsen, Birger, Alstrup, Stephen, Lioma, Christina
We study whether it is possible to infer if a news headline is true or false using only the movement of the human eyes when reading news headlines. Our study with 55 participants who are eye-tracked when reading 108 news headlines (72 true, 36 false)
Externí odkaz:
http://arxiv.org/abs/2006.09736
Content-aware recommendation approaches are essential for providing meaningful recommendations for \textit{new} (i.e., \textit{cold-start}) items in a recommender system. We present a content-aware neural hashing-based collaborative filtering approac
Externí odkaz:
http://arxiv.org/abs/2006.00617
In this paper we consider the problem of modelling when students end their session in an online mathematics educational system. Being able to model this accurately will help us optimize the way content is presented and consumed. This is done by model
Externí odkaz:
http://arxiv.org/abs/1909.06856
Publikováno v:
In Proceedings of the 11'th International Conference on Educational Data Mining (EDM), p. 280-285. 2018
Analysis of log data generated by online educational systems is an essential task to better the educational systems and increase our understanding of how students learn. In this study we investigate previously unseen data from Clio Online, the larges
Externí odkaz:
http://arxiv.org/abs/1908.08937
In this paper we do the first large scale analysis of writing style development among Danish high school students. More than 10K students with more than 100K essays are analyzed. Writing style itself is often studied in the natural language processin
Externí odkaz:
http://arxiv.org/abs/1906.03072
Publikováno v:
Proceedings. ESANN 2019: 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. ed. Michel Verleysen. 2019. p 197-202
Students hiring ghostwriters to write their assignments is an increasing problem in educational institutions all over the world, with companies selling these services as a product. In this work, we develop automatic techniques with special focus on d
Externí odkaz:
http://arxiv.org/abs/1906.01635
Fast similarity search is a key component in large-scale information retrieval, where semantic hashing has become a popular strategy for representing documents as binary hash codes. Recent advances in this area have been obtained through neural netwo
Externí odkaz:
http://arxiv.org/abs/1906.00671
Word embeddings predict a word from its neighbours by learning small, dense embedding vectors. In practice, this prediction corresponds to a semantic score given to the predicted word (or term weight). We present a novel model that, given a target wo
Externí odkaz:
http://arxiv.org/abs/1906.00674