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@inproceedings{884893, author = {Řehůřek, Radim and Sojka, Petr}, address = {Valletta, Malta}, booktitle = {Proceedings of LREC 2010 workshop New Challenges for NLP Frameworks}, keywords = {document similarity; NLP; software; vector space model; topical modelling; software framework; topical document similarity; Python; IR; LSA; LDA; gensim; DML-CZ}, howpublished = {paměťový nosič}, language = {eng}, location = {Valletta, Malta}, isbn = {2-9517408-6-7}, pages = {46--50}, publisher = {University of Malta}, title = {Software Framework for Topic Modelling with Large Corpora}, url = {http://www.lrec-conf.org/proceedings/lrec2010/workshops/W10.pdf}, year = {2010} }
TY - JOUR ID - 884893 AU - Řehůřek, Radim - Sojka, Petr PY - 2010 TI - Software Framework for Topic Modelling with Large Corpora PB - University of Malta CY - Valletta, Malta SN - 2951740867 KW - document similarity KW - NLP KW - software KW - vector space model KW - topical modelling KW - software framework KW - topical document similarity KW - Python KW - IR KW - LSA KW - LDA KW - gensim KW - DML-CZ UR - http://www.lrec-conf.org/proceedings/lrec2010/workshops/W10.pdf L2 - http://www.fi.muni.cz/usr/sojka/papers/lrec2010-rehurek-sojka.pdf N2 - Large corpora are ubiquitous in today's world and memory quickly becomes the limiting factor in practical applications of the Vector Space Model (VSM). We identify gap in existing VSM implementations, 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. In 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. ER -
ŘEHŮŘEK, Radim a Petr SOJKA. Software Framework for Topic Modelling with Large Corpora. In \textit{Proceedings of LREC 2010 workshop New Challenges for NLP Frameworks}. Valletta, Malta: University of Malta, 2010, s.~46--50. ISBN~2-9517408-6-7.
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