SentenceEmbedder: Sentence Embedder using Word Vectors

In VectrixDB: Lightweight Vector Database with Embedded Machine Learning Models

Sentence Embedder using Word Vectors

Description

Creates sentence embeddings by averaging word vectors with IDF weighting

Public fields

dim

Embedding dimension

vocab_size

Vocabulary size

Methods

Public methods

• SentenceEmbedder$new()

• SentenceEmbedder$fit()

• SentenceEmbedder$embed()

• SentenceEmbedder$get_word_vector()

• SentenceEmbedder$has_word()

• SentenceEmbedder$most_similar()

• SentenceEmbedder$clone()

---

Method new()

Create a new SentenceEmbedder

Usage

SentenceEmbedder$new(word_vectors, use_idf = TRUE, smooth_idf = 1)

Arguments

word_vectors

WordVectors object from load_word_vectors()

use_idf

Use IDF weighting (recommended)

smooth_idf

Smoothing for IDF

---

Method fit()

Fit IDF weights on a corpus

Usage

SentenceEmbedder$fit(texts)

Arguments

texts

Character vector of texts

---

Method embed()

Embed texts to sentence vectors

Usage

SentenceEmbedder$embed(texts)

Arguments

texts

Character vector of texts

Returns

Matrix of embeddings (rows are sentences)

---

Method get_word_vector()

Get word vector for a single word

Usage

SentenceEmbedder$get_word_vector(word)

Arguments

word

Word to look up

Returns

Numeric vector or NULL if not found

---

Method has_word()

Check if word is in vocabulary

Usage

SentenceEmbedder$has_word(word)

Arguments

word

Word to check

Returns

Logical

---

Method most_similar()

Find most similar words

Usage

SentenceEmbedder$most_similar(word, n = 10)

Arguments

word

Query word

n

Number of results

Returns

Data frame with word and similarity

---

Method clone()

The objects of this class are cloneable with this method.

Usage

SentenceEmbedder$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

VectrixDB documentation built on Feb. 20, 2026, 5:09 p.m.