We just launched our courses -> Start learning today ✨

Join
Login

Top2Vec

ML Models & Algorithms
An embedding-based topic model noted for scaling efficiently to very large datasets, sometimes preferred over BERTopic when speed on large data is crucial.

Top2Vec is an Embedding-Based Approach to Topic Modeling that uses document embeddings to discover topic clusters. It is cited as a competing model to BERTopic.
Top2Vec is noted for being optimized for scaling to very large datasets efficiently, allowing it to handle millions of documents. However, compared to BERTopic, Top2Vec offers more limited choices in embedding solutions (originally using Doc2Vec or universal sentence embeddings) and may produce topics that are sometimes overlapping or mixed concepts. In scenarios focused purely on speed with massive data, Top2Vec may have an advantage over BERTopic due to the latter’s computational overhead.

Related Concepts

HDBSCAN

Sources & References

Introduction to Machine Learning for SEOs Course
academy.mlforseo.com

Explore other ML Models & Algorithms terms

B
BERT (Bidirectional Encoder Representations from Transformers)
The foundational language model used for transformer-based embeddings in BERTopic.
B
BERTopic
An unsupervised machine learning approach for topic modeling that generates interpretable topics and performs dynamic…
B
BERTopic
An unsupervised machine learning approach for topic modeling that generates interpretable topics and performs dynamic…
B
BIRCH (Balanced Iterative Hierarchical Based Clustering)
A hierarchical clustering method efficient for large datasets and time series.
B
Boyer-Moore
An exact string-matching algorithm and one of the best-known pattern recognition algorithms.
C
c-TF-IDF
Class-based Term Frequency-Inverse Document Frequency; used by BERTopic for clearer topic representation and selection of…
D
DBSCAN
Density-Based Spatial Clustering of Applications with Noise; groups data points based on density. Useful for…
D
Decision Tree
An early, simple model for classification or regression.
D
Distance-based matching
Fuzzy matching methods focusing on "edit distance" rather than exact spelling.
D
DistilBERT (Refined Query Semantic Class Classifier)
A fine-tuned BERT model used for semantic class classification based on queries.
E
Encoder Model
A machine learning model used in Google's two-step process for building and maintaining the Knowledge…
F
Fuzzy Matching / Fuzzy String Matching
A string similarity assessment approach, typically relying on character distance rather than semantics, used to…