Titlebook

Disaster

Progesterone

https://doi.org/10.1007/978-3-030-14405-0n are native to MMR, unlike other more classical maximum margin approaches, like SVM. We have tested our approach with the ImageCLEF 2015 multi-label classification task, Pascal VOC and Flickr dataset.

hemoglobin

anarchist

Reranking Hypotheses of Machine-Translated Queries for Cross-Lingual Information Retrievale-learning method trained to directly optimize retrieval quality. We experiment with various types of features and the results obtained on the medical-domain test collection from the CLEF eHealth Lab series show significant improvement of retrieval quality compared to a system using single translation provided by MT.

insurrection

extinguish

A Product Feature-Based User-Centric Ranking Model for E-Commerce Searchentric model for product search involving, in addition to product characteristics, the user engagement toward the product. This model has been evaluated through the product search track of the LL4IR lab at CLEF 2015 in order to highlight the effectiveness of our model as well as the impact of the user engagement factor.

extinguish

分解

Landmarks for Spatial Developmentaking comparisons between different recommender systems. The experiments aim to quantify the expected degree of variation in performance that cannot be attributed to differences between systems. We classify and discuss the non-algorithmic causes of performance differences observed.

outset

Oratory