English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, we present the methodology and the results obtained by ourteams, dubbed Blue Man Group, in the ASSIN (from the Portuguese {\itAvalia\c{c}\~ao de Similaridade Sem\^antica e Infer\^encia Textual})competition, held at PROPOR 2016\footnote{International Conference on theComputational Processing of the Portuguese Language -http://propor2016.di.fc.ul.pt/}. Our team's strategy consisted of evaluatingmethods based on semantic word vectors, following two distinct directions: 1)to make use of low-dimensional, compact, feature sets, and 2) deeplearning-based strategies dealing with high-dimensional feature vectors.Evaluation results demonstrated that the first strategy was more promising, sothat the results from the second strategy have been discarded. As a result, byconsidering the best run of each of the six teams, we have been able to achievethe best accuracy and F1 values in entailment recognition, in the BrazilianPortuguese set, and the best F1 score overall. In the semantic similarity task,our team was ranked second in the Brazilian Portuguese set, and thirdconsidering both sets.

Methodology and Results for the Competition on Semantic Similarity Evaluation and Entailment Recognition for PROPOR 2016