ŘEHŮŘEK, Radim and Petr SOJKA. Software Framework for Topic Modelling with Large Corpora. In Proceedings of LREC 2010 workshop New Challenges for NLP Frameworks. Valletta, Malta: University of Malta, 2010, p. 46--50. ISBN 2-9517408-6-7.
Other formats:   BibTeX LaTeX RIS
Basic information
Original name Software Framework for Topic Modelling with Large Corpora
Name in Czech Softwarový framework pro tematickou podobnost ve velkých korpusech
Authors ŘEHŮŘEK, Radim (203 Czech Republic, belonging to the institution) and Petr SOJKA (203 Czech Republic, guarantor, belonging to the institution).
Edition Valletta, Malta, Proceedings of LREC 2010 workshop New Challenges for NLP Frameworks, p. 46--50, 5 pp. 2010.
Publisher University of Malta
Other information
Original language English
Type of outcome Proceedings paper
Field of Study Computer hardware and software
Country of publisher Malta
Confidentiality degree is not subject to a state or trade secret
Publication form storage medium (CD, DVD, flash disk)
WWW URL URL URL URL
RIV identification code RIV/00216224:14330/10:00043991
Organization Fakulta informatiky – Repository – Repository
ISBN 2-9517408-6-7
Keywords (in Czech) podobnost dokumentů; NLP; software; vektorový model dokumentů; softwarový framework; tematická podobnost dokumentů; Python; IR; LSA; LDA; gensim; DML-CZ
Keywords in English document similarity; NLP; software; vector space model; topical modelling; software framework; topical document similarity; Python; IR; LSA; LDA; gensim; DML-CZ
Links LA09016, research and development project. MUNI/E/0084/2009, interní kód Repo. 2C06009, research and development project.
Changed by Changed by: RNDr. Daniel Jakubík, učo 139797. Changed: 1/9/2020 11:34.
Abstract
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.
Abstract (in Czech)
Velké korpusy jsou dnes všudypřítomné. Při jejich plnotextovém zpracování ve vektorové reprezentaci (podobnost dokumentů) brzy začne být limitujícím faktorem velikost paměti. Identifikovali jsme a zaplnili mezeru v dobře škálovatelné implementaci několika populárních algoritmů. Popisujeme snadno použitelný NLP softwarový framework založený na myšlence proudového zpracování dokumentů, tedy zpracování jednoho dokumentu po druhém, tedy v konstatní paměti vzhledem k počtu dokumentů. Implementujeme několik populárních algoritmů pro tematickou inferenci, včetně Latentní sémantické analýzy a Latentní Dirichletovy alokace způsobem, který je nezávislý na velikosti korpusu. Důraz je kladen na přímočarý a intuitivní design, aby modifikace a rozšíření metod a jejich užití v praxi bylo co nejjednodušší. Demonstrujeme užitečnost našeho přístupu na nasazení software na příkladu počítání podobností dokumentů v existující digitální matematické knihovně DML-CZ.
Type Name Uploaded/Created by Uploaded/Created Rights
lrec2010-rehurek-sojka.pdf Licence Creative Commons  File version 9/1/2013

Properties

Name
lrec2010-rehurek-sojka.pdf
Address within IS
https://repozitar.cz/auth/repo/15725/71943/
Address for the users outside IS
https://repozitar.cz/repo/15725/71943/
Address within Manager
https://repozitar.cz/auth/repo/15725/71943/?info
Address within Manager for the users outside IS
https://repozitar.cz/repo/15725/71943/?info
Uploaded/Created
Wed 9/1/2013 11:42

Rights

Right to read
  • anyone on the Internet
Right to upload
 
Right to administer:
  • a concrete person RNDr. Daniel Jakubík, uco 139797
  • a concrete person Mgr. Ľuboš Lunter, uco 143320
Attributes
 
lrec2010-rehurek-sojka.pdf Licence Creative Commons  File version 1/9/2020

Properties

Name
lrec2010-rehurek-sojka.pdf
Address within IS
https://repozitar.cz/auth/repo/15725/892697/
Address for the users outside IS
https://repozitar.cz/repo/15725/892697/
Address within Manager
https://repozitar.cz/auth/repo/15725/892697/?info
Address within Manager for the users outside IS
https://repozitar.cz/repo/15725/892697/?info
Uploaded/Created
Tue 1/9/2020 11:34

Rights

Right to read
  • anyone on the Internet
Right to upload
 
Right to administer:
  • a concrete person Mgr. Lucie Vařechová, uco 106253
  • a concrete person RNDr. Daniel Jakubík, uco 139797
  • a concrete person Mgr. Jolana Surýnková, uco 220973
Attributes
 
Print
Add to clipboard Displayed: 16/8/2024 14:14