Contents
What is semantic similarity?
Semantic similarity, variously also called “semantic closeness /proximity/nearness” is a concept whereby a set of documents or terms within term lists are assigned a metric based on the likeness of their meaning/semantic content.
What is sentence similarity?
Word order similarity is a way to assess sentences simi- larity considering order of words. Two sentences are typically similar if same words exist in both sentences in the same order. However, sentences should be considered as not completely similar if words of a sentence have dif- ferent order as the other sentence.
Why is semantic similarity important?
Semantic similarity measures have been applied and developed in biomedical ontologies. They are mainly used to compare genes and proteins based on the similarity of their functions rather than on their sequence similarity, but they are also being extended to other bioentities, such as diseases.
Which is the best use of semantic similarity?
A popular use case of semantic similarity is to find the top most relevant sentences in a corpus given a query sentence. This can also be called as semantic search. To conduct semantic search, we will need a corpus of sentences and a sentence that acts as the query.
How to compute similarity between two words with similar meaning?
Two words with similar meaning would have similar vectors allowing us to compute vector similarities. Extending this idea, in the vector space, we should be able to compute the similarity between any two sentences. And this is what sentence embedding models achieve.
Can you use Bert to measure semantic similarity?
An important note here is that BERT is not trained for semantic sentence similarity directly like the Universal Sentence Encoder or InferSent models. Therefore, BERT embeddings cannot be used directly to apply cosine distance to measure similarity.
Which is the most similar sentence in the world?
(The Hill) (Score: 0.7472) You can see how uncannily accurate the model is able to pick out the most similar sentences. The example above is simple, but illustrates an important point of semantic search. It would take a human couple of minutes to find the most-similar sentences.