Search Results for author: Ioannis Partalas

Found 12 papers, 2 papers with code

Aligning Hotel Embeddings using Domain Adaptation for Next-Item Recommendation

no code implementations31 Aug 2021 Ioannis Partalas

The results show that the proposed approach can align the two embedding spaces while achieving good performance in both brands.

Domain Adaptation

Wasserstein distances for evaluating cross-lingual embeddings

no code implementations24 Oct 2019 Georgios Balikas, Ioannis Partalas

Word embeddings are high dimensional vector representations of words that capture their semantic similarity in the vector space.

Cross-Lingual Document Classification Document Classification +4

Comparing Named-Entity Recognizers in a Targeted Domain: Handcrafted Rules vs Machine Learning

no code implementations JEPTALNRECITAL 2016 Ioannis Partalas, C{\'e}dric Lopez, Fr{\'e}d{\'e}rique Segond

Comparing Named-Entity Recognizers in a Targeted Domain : Handcrafted Rules vs. Machine Learning Named-Entity Recognition concerns the classification of textual objects in a predefined set of categories such as persons, organizations, and localizations.

BIG-bench Machine Learning named-entity-recognition +2

e-Commerce product classification: our participation at cDiscount 2015 challenge

no code implementations9 Jun 2016 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.

General Classification text-classification +1

LSHTC: A Benchmark for Large-Scale Text Classification

no code implementations30 Mar 2015 Ioannis Partalas, Aris Kosmopoulos, Nicolas Baskiotis, Thierry Artieres, George Paliouras, Eric Gaussier, Ion Androutsopoulos, Massih-Reza Amini, Patrick Galinari

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 thousands).

General Classification text-classification +1

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