136 citations · 154 across the 5 of their papers we have counts for
6 papers
Aligning Hotel Embeddings using Domain Adaptation for Next-Item Recommendation
Ioannis Partalas
In online platforms it is often the case to have multiple brands under the same group which may target different customer profiles, or have different domains. For example, in the h…
Wasserstein distances for evaluating cross-lingual embeddings
Georgios Balikas, Ioannis Partalas
Word embeddings are high dimensional vector representations of words that capture their semantic similarity in the vector space. There exist several algorithms for learning such em…
Hotel2vec: Learning Attribute-Aware Hotel Embeddings with Self-Supervision
Ali Sadeghian, Shervin Minaee, Ioannis Partalas +3
We propose a neural network architecture for learning vector representations of hotels. Unlike previous works, which typically only use user click information for learning item emb…
CAp 2017 challenge: Twitter Named Entity Recognition
Cédric Lopez, Ioannis Partalas, Georgios Balikas +5
The paper describes the CAp 2017 challenge. The challenge concerns the problem of Named Entity Recognition (NER) for tweets written in French. We first present the data preparation…
e-Commerce product classification: our participation at cDiscount 2015 challenge
Ioannis Partalas, Georgios Balikas
This report describes our participation in the cDiscount 2015 challenge where the goal was to classify product items in a predefined taxonomy of products. Our best submission yield…
LSHTC: A Benchmark for Large-Scale Text Classification
Ioannis Partalas, Aris Kosmopoulos, Nicolas Baskiotis +6
LSHTC is a series of challenges which aims to assess the performance of classification systems in large-scale classification in a a large number of classes (up to hundreds of thous…