2010 SoftwareFrameworkforTopicModell
- (Rehurek & Sojka, 2010) ⇒ Radim Rehurek, and Petr Sojka. (2010). “Software Framework for Topic Modelling with Large Corpora.” In: Proceedings of the LREC 2010 workshop on new challenges for NLP frameworks.
Subject Headings: Word Embedding System; Gensim
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Abstract
Large corpora are ubiquitous in todayâs world and memory quickly becomes the limiting factor in practical applications of the Vector Space Model (VSM). In this paper, we identify a gap in existing implementations of many of the popular algorithms, which is their scalability and ease of use. We describe a Natural Language Processing software framework which is based on the idea of document streaming, i.e. processing corpora document after document, in a memory independent fashion. Within this framework, we implement several popular algorithms for topical inference, including Latent Semantic Analysis and Latent Dirichlet Allocation, in a way that makes them completely independent of the training corpus size. Particular emphasis is placed on straightforward and intuitive framework design, so that modifications and extensions of the methods and/or their application by interested practitioners are effortless. We demonstrate the usefulness of our approach on a real-world scenario of computing document similarities within an existing digital library DML-CZ. 1.
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2010 SoftwareFrameworkforTopicModell | Radim Rehurek Petr Sojka | Software Framework for Topic Modelling with Large Corpora | 2010 |