BACKGROUND Predicting protein function from primary sequence is an important open problem in modern biology. Not only are there many thousands of proteins of unknown function, current approaches for predicting function must be improved upon. One problem in particular is overly-specific function predictions which we address here with a new statistical model of the relationship between protein se...

There are at least two kinds of similarity. Relational similarity is correspondence between relations, in contrast with attributional similarity, which is correspondence between attributes. When two words have a high degree of attributional similarity, we call them synonyms. When two pairs of words have a high degree of relational similarity, we say that their relations are analogous. For examp...

In this paper, we present an approach for merging fine-grained verb senses of Hindi WordNet. Senses are merged based on gloss similarity score. We explore the use of word embeddings for gloss similarity computation and compare with various WordNet based gloss similarity measures. Our results indicate that word embeddings show significant improvement over WordNet based measures. Consequently, we...

We describe three semantic text similarity systems developed for the *SEM 2013 STS shared task and the results of the corresponding three runs. All of them shared a word similarity feature that combined LSA word similarity and WordNet knowledge. The first, which achieved the best mean score of the 89 submitted runs, used a simple term alignment algorithm augmented with penalty terms. The other ...

This paper proposes to use distributed representation of words (word embeddings) in cross-language textual similarity detection. The main contributions of this paper are the following: (a) we introduce new cross-language similarity detection methods based on distributed representation of words; (b) we combine the different methods proposed to verify their complementarity and finally obtain an o...

Machine translation translates a speech of text from the source language to target language. This paper introduces machine translation evaluation by calculating the semantic textual similarity between the machine translated sentences. The similarity score varies by using different values of alpha, beta and ranges semantic similarity [0,5]. The experiment is carried out on SemEval 2017 datasets....

The paper describes an image matching method based on visual attention and SURF keypoints. Biologically inspired visual attention system is used to guide local interest point detection. Interest points are represented with SURF descriptors. One–to–one symmetric search is performed on descriptors to select a set of matched interest point pairs. Pairs are then weighted according to attention dist...