Abstract : We report our participation to the multi-modal Spatial Role Labeling (mSpRL) lab at CLEF 2017. The task consists in extracting and classifying spatial relationships from textual data and associated images. Our approach focuses on the classification part as we use a base-line system for the extraction of the relations: we train a linear Support Vector Machine (SVM) model to classify hand-crafted vectors representing spatial relations. We present the obtained experiments and discuss also the effect of model parameters. Finally, we conclude the paper and introduce ideas for future developments.
https://hal.sorbonne-universite.fr/hal-01579493
Contributeur : Eloi Zablocki
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Soumis le : jeudi 31 août 2017 - 11:29:12
Dernière modification le : vendredi 31 août 2018 - 09:25:57
Document(s) archivé(s) le : vendredi 1 décembre 2017 - 18:09:21
Éloi Zablocki, Patrick Bordes, Laure Soulier, Benjamin Piwowarski, Patrick Gallinari. LIP6@CLEF2017: Multi-Modal Spatial Role Labeling using Word Embeddings Working notes. CLEF 2017, 2017, Dublin, Ireland. CLEF 2017 Working Notes. 〈hal-01579493〉
