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Lbl2Vec: An Embedding-Based Approach for Unsupervised Document Retrieval
  on Predefined Topics

Lbl2Vec: An Embedding-Based Approach for Unsupervised Document Retrieval on Predefined Topics

12 October 2022
Tim Schopf
Daniel Braun
Florian Matthes
ArXivPDFHTML

Papers citing "Lbl2Vec: An Embedding-Based Approach for Unsupervised Document Retrieval on Predefined Topics"

6 / 6 papers shown
Title
Top2Vec: Distributed Representations of Topics
Top2Vec: Distributed Representations of Topics
D. Angelov
73
347
0
19 Aug 2020
Benchmarking Zero-shot Text Classification: Datasets, Evaluation and
  Entailment Approach
Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach
Wenpeng Yin
Jamaal Hay
Dan Roth
163
548
0
31 Aug 2019
An Empirical Evaluation of doc2vec with Practical Insights into Document
  Embedding Generation
An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation
Jey Han Lau
Timothy Baldwin
133
652
0
19 Jul 2016
Document Embedding with Paragraph Vectors
Document Embedding with Paragraph Vectors
Andrew M. Dai
C. Olah
Quoc V. Le
144
373
0
29 Jul 2015
Distributed Representations of Sentences and Documents
Distributed Representations of Sentences and Documents
Quoc V. Le
Tomas Mikolov
FaML
254
9,242
0
16 May 2014
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomas Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
677
31,512
0
16 Jan 2013
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