Back to search

Article

Effect of dimension size and window size on word embedding in classification tasks

2024-07-08

Abstract excerpt

<title>Abstract</title> <p>In natural language processing, there are several approaches to transform text into multi-dimensional word vectors, such as TF-IDF (term frequency - inverse document frequency), Word2Vec, GloVe (Global Vectors), which are widely used to this day. The meaning of a word in Word2Vec and GloVe models represents its context. Syntactic or semantic relationships between words are preserved, an...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
d04a33be-2967-5048-be9a-f94f9472a66f
DOI
10.21203/rs.3.rs-4532901/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Effect of dimension size and window size on word embedding in classification tasksDOI 10.21203/rs.3.rs-4532901/v1
Select a neighboring publication to make it the new centre.