This project sought to enhance the natural language processing research of the MTA SZTAKI institute in Budapest, Hungary, by extending their semantic textual similarity system to evaluate Spanish sentences. Language analysis resources were collected to generate a working system to analyze similarities between Spanish sentence pairs. This system was based on that which the institute had previously developed for English. The final system was tested against large data sets of sentence pairs, and compared to a Gold Standard of scores created by human linguists, with the goal of having a high correlation between the two data sets
We present in this paper our system developed for SemEval 2015 Shared Task 2 (2a - English Semantic ...
STS corpus is a benchmark for evaluating Semantic Text Similarity in Catalan. It consists of 3079 se...
Semantic Textual Similarity (STS) measures the degree of semantic equivalence between two texts. Thi...
International audienceWe present our submitted systems for Semantic Textual Similarity (STS) Track 4...
This paper presents an approach for estimat-ing the Semantic Textual Similarity of full English sent...
In this paper we describe the specifications and results of UMCC_DLSI system, which was involved in ...
In many natural language understanding applications, text processing requires comparing lexical unit...
This paper presents an overlap-based ap-proach using bag of words and the Spanish WordNet to solve t...
Shared Task 1 at SemEval-2017 deals with assessing the semantic similarity between sentences, either...
Shared Task 1 at SemEval-2017 deals with assessing the semantic similarity between sentences, either...
User acceptance of artificial intelligence agents might depend on their ability to explain their rea...
This paper presents a grammar and semantic corpus based similarity algorithm for natural language se...
This research addresses the problem of deriving semantic similarity between words of language using ...
Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include...
Sentence similarity measures play an increasingly important role in text-related research and applic...
We present in this paper our system developed for SemEval 2015 Shared Task 2 (2a - English Semantic ...
STS corpus is a benchmark for evaluating Semantic Text Similarity in Catalan. It consists of 3079 se...
Semantic Textual Similarity (STS) measures the degree of semantic equivalence between two texts. Thi...
International audienceWe present our submitted systems for Semantic Textual Similarity (STS) Track 4...
This paper presents an approach for estimat-ing the Semantic Textual Similarity of full English sent...
In this paper we describe the specifications and results of UMCC_DLSI system, which was involved in ...
In many natural language understanding applications, text processing requires comparing lexical unit...
This paper presents an overlap-based ap-proach using bag of words and the Spanish WordNet to solve t...
Shared Task 1 at SemEval-2017 deals with assessing the semantic similarity between sentences, either...
Shared Task 1 at SemEval-2017 deals with assessing the semantic similarity between sentences, either...
User acceptance of artificial intelligence agents might depend on their ability to explain their rea...
This paper presents a grammar and semantic corpus based similarity algorithm for natural language se...
This research addresses the problem of deriving semantic similarity between words of language using ...
Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include...
Sentence similarity measures play an increasingly important role in text-related research and applic...
We present in this paper our system developed for SemEval 2015 Shared Task 2 (2a - English Semantic ...
STS corpus is a benchmark for evaluating Semantic Text Similarity in Catalan. It consists of 3079 se...
Semantic Textual Similarity (STS) measures the degree of semantic equivalence between two texts. Thi...