An Ontology-Based Recommender System with an Application to the Star Trek Television Franchise

1 code implementation • 31 Jul 2018 • Paul Sheridan, Mikael Onsjö, Claudia Becerra, Sergio Jimenez, George Dueñas

As a study case, we evaluated the proposed method against other approaches by performing the classical rating prediction task on a collection of Star Trek television series episodes in an item cold-start scenario.

Collaborative Filtering Recommendation Systems +1

UNAL: Discriminating between Literal and Figurative Phrasal Usage Using Distributional Statistics and POS tags

no code implementations • SEMEVAL 2013 • Sergio Jimenez, Claudia Becerra, Alex Gelbukh, er

Information Retrieval Machine Translation +1

SOFTCARDINALITY: Learning to Identify Directional Cross-Lingual Entailment from Cardinalities and SMT

no code implementations • SEMEVAL 2013 • Sergio Jimenez, Claudia Becerra, Alex Gelbukh, er

Machine Translation Natural Language Inference

SOFTCARDINALITY-CORE: Improving Text Overlap with Distributional Measures for Semantic Textual Similarity

no code implementations • SEMEVAL 2013 • Sergio Jimenez, Claudia Becerra, Alex Gelbukh, er

Information Retrieval Machine Translation +3

SOFTCARDINALITY: Hierarchical Text Overlap for Student Response Analysis

no code implementations • SEMEVAL 2013 • Sergio Jimenez, Claudia Becerra, Alex Gelbukh, er

Entity Resolution Information Retrieval +2

Soft Cardinality + ML: Learning Adaptive Similarity Functions for Cross-lingual Textual Entailment

no code implementations • SEMEVAL 2012 • Sergio Jimenez, Claudia Becerra, Alex Gelbukh, er

Information Retrieval Natural Language Inference

Soft Cardinality: A Parameterized Similarity Function for Text Comparison

no code implementations • SEMEVAL 2012 • Sergio Jimenez, Claudia Becerra, Alex Gelbukh, er