Corpus-basedand Knowledge-based Measures of Text Semantic Similarity

AAAI Conferences

This paper presents a method for measuring the semantic similarity of texts, using corpus-based and knowledge-based measures of similarity. Previous work on this problem has focused mainly on either large documents (e.g.


Structural Sentence Similarity Estimation for Short Texts

AAAI Conferences

Sentence similarity is the basis of most text-related tasks. In this paper, we define a new task of sentence similarity estimation specifically for short while informal, social-network styled sentences. The new type of sentence similarity, which we call Structural Similarity, eliminates syntactic or grammatical features such as dependency paths and Part-of-Speech (POS) tagging which do not have enough representativeness on short sentences. Structural Similarity does not consider actual meanings of the sentences either but puts more emphasis on the similarities of sentence structures, so as to discover purpose- or emotion-level similarities. The idea is based on the observation that people tend to use sentences with similar structures to express similar feelings. Besides the definition, we present a new feature set and a mechanism to calculate the scores, and, for the needs of disambiguating word senses we propose a variant of the Word2Vec model to represent words. We prove the correctness and advancement of our sentence similarity measurement by experiments.


Calculate Cosine Similarity Using Scipy – Data Sets & Sample Code

@machinelearnbot

Cosine Similarity is a measure of similarity between two vectors that calculates the cosine of the angle between them. We have shared data sets, sample code & an example case study in implementing Cosine Similarity. We are looking to find a place to settle down in California. We like a place called Montecito, CA and want to find similar towns & cities to look for places. How would we go about doing it?



Calculate Cosine Similarity Using Scipy – Data Sets & Sample Code

@machinelearnbot

Cosine Similarity is a measure of similarity between two vectors that calculates the cosine of the angle between them. We have shared data sets, sample code & an example case study in implementing Cosine Similarity. We are looking to find a place to settle down in California. We like a place called Montecito, CA and want to find similar towns & cities to look for places. How would we go about doing it?