KOSHIK: A large-scale distributed computing framework for NLP
(2014) 3rd International Conference on Pattern Recognition Applications an Methods (ICPRAM 2014) p.464-470- Abstract
- In this paper, we describe KOSHIK, an end-to-end framework to process the unstructured natural language content of multilingual documents. We used the Hadoop distributed computing infrastructure to build this framework as it enables KOSHIK to easily scale by adding inexpensive commodity hardware. We designed an annotation model that allows the processing algorithms to incrementally add layers of annotation without modifyingtheoriginaldocument. We used the Avro binary format to serialize th edocuments. Avro is designed for Hadoop and allows other data warehousing tools to directly query the documents. This paper reports the implementation choices and details of the framework,the annotation model,the options for querying processed data, and... (More)
- In this paper, we describe KOSHIK, an end-to-end framework to process the unstructured natural language content of multilingual documents. We used the Hadoop distributed computing infrastructure to build this framework as it enables KOSHIK to easily scale by adding inexpensive commodity hardware. We designed an annotation model that allows the processing algorithms to incrementally add layers of annotation without modifyingtheoriginaldocument. We used the Avro binary format to serialize th edocuments. Avro is designed for Hadoop and allows other data warehousing tools to directly query the documents. This paper reports the implementation choices and details of the framework,the annotation model,the options for querying processed data, and the parsing results on the English and Swedish editions of Wikipedia.
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Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4352684
- author
- Exner, Peter LU and Nugues, Pierre LU
- organization
- publishing date
- 2014
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 3rd International Conference on Pattern Recognition Applications and Methods (ICPRAM 2014)
- pages
- 464 - 470
- publisher
- SciTePress
- conference name
- 3rd International Conference on Pattern Recognition Applications an Methods (ICPRAM 2014)
- conference location
- Angers, France
- conference dates
- 2014-03-06 - 2014-03-08
- external identifiers
-
- scopus:84902310568
- ISBN
- 978-989-758-018-5
- language
- English
- LU publication?
- yes
- id
- c9fc300c-af19-4b87-be5b-e4547075d01a (old id 4352684)
- date added to LUP
- 2016-04-04 14:00:12
- date last changed
- 2022-01-30 17:05:49
@inproceedings{c9fc300c-af19-4b87-be5b-e4547075d01a, abstract = {{In this paper, we describe KOSHIK, an end-to-end framework to process the unstructured natural language content of multilingual documents. We used the Hadoop distributed computing infrastructure to build this framework as it enables KOSHIK to easily scale by adding inexpensive commodity hardware. We designed an annotation model that allows the processing algorithms to incrementally add layers of annotation without modifyingtheoriginaldocument. We used the Avro binary format to serialize th edocuments. Avro is designed for Hadoop and allows other data warehousing tools to directly query the documents. This paper reports the implementation choices and details of the framework,the annotation model,the options for querying processed data, and the parsing results on the English and Swedish editions of Wikipedia.<br/>}}, author = {{Exner, Peter and Nugues, Pierre}}, booktitle = {{3rd International Conference on Pattern Recognition Applications and Methods (ICPRAM 2014)}}, isbn = {{978-989-758-018-5}}, language = {{eng}}, pages = {{464--470}}, publisher = {{SciTePress}}, title = {{KOSHIK: A large-scale distributed computing framework for NLP}}, url = {{https://lup.lub.lu.se/search/files/19728738/4352694.pdf}}, year = {{2014}}, }