Cited By
View all- Pareed AIdicula S(2019)A Relation Extraction System for Indian LanguagesAdvances in Science, Technology and Engineering Systems Journal10.25046/aj0402084:2(65-69)Online publication date: 2019
Information Extraction for Conversational Systems in Indian Languages - Arnekt IECSIL
Authors: 
Barathi Ganesh HB, Soman KP, Reshma U, Mandar Kale, Prachi Mankame, Gouri Kulkarni, Anitha Kale, Anand Kumar MAuthors Info & Claims
Pages 18 - 20
Abstract
Data being the new source of wealth, mining intelligence from every possible units of it, has become today's salient feature in many fields. Text data is not limited to one language and this has showcased its usability in creating multiple applications from various languages. Development of Indian languages is just getting better both in terms of resource and application specific. Information Extraction for Conversational Systems in Indian Languages - Arnekt IECSIL has taken its step in creating its own resource in Indian languages (Hindi, Kannada, Malayalam, Tamil and Telugu) for Named Entity Recognition (NER) and Information Extraction (IE) tasks. This overview paper will be detailing more on the existing Indian language corpora development and the steps taken for building our own corpus along with its statistics.
References
[1]
Brijesh Bhatt and Pushpak Bhattacharyya. 2012. Domain specific ontology extractor for indian languages. In Proceedings of the 10th Workshop on Asian Language Resources. 75--84.
[2]
VV Devadath and Dipti Misra Sharma. 2016. Significance of an accurate sandhi-splitter in shallow parsing of dravidian languages. In Proceedings of the ACL 2016 Student Research Workshop. 37--42.
[3]
Hyderabad International Institute of Information Technology. {n. d.}. Tamil Shallow Parser. ({n. d.}).
[4]
Dinesh Kumar and Gurpreet Singh Josan. 2010. Part of speech taggers for morphologically rich indian languages: a survey. International Journal of Computer Applications 6, 5 (2010), 32--41.
[5]
Animesh Nayan, B Ravi Kiran Rao, Pawandeep Singh, Sudip Sanyal, and Ratna Sanyal. 2008. Named entity recognition for Indian languages. In Proceedings of the IJCNLP-08 Workshop on Named Entity Recognition for South and South East Asian Languages.
[6]
Siva Reddy and Serge Sharoff. 2011. Cross language POS taggers (and other tools) for Indian languages: An experiment with Kannada using Telugu resources. In Proceedings of the Fifth International Workshop On Cross Lingual Information Access. 11--19.
Recommendations
A Flexible Text Mining System for Entity and Relation Extraction in PubMed
DTMBIO '15: Proceedings of the ACM Ninth International Workshop on Data and Text Mining in Biomedical InformaticsDue to an enormous number of scientific publications that cannot be handled manually, there is a rising interest in text-mining techniques for automated information extraction, especially in the biomedical field. Such techniques provide effective means ...
Transliteration normalization for Information Extraction and Machine Translation
Foreign name transliterations typically include multiple spelling variants. These variants cause data sparseness and inconsistency problems, increase the Out-of-Vocabulary (OOV) rate, and present challenges for Machine Translation, Information ...
Learning multilingual named entity recognition from Wikipedia
We automatically create enormous, free and multilingual silver-standard training annotations for named entity recognition (ner) by exploiting the text and structure of Wikipedia. Most ner systems rely on statistical models of annotated data to identify ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
December 2018
68 pages
ISBN:9781450362085
DOI:10.1145/3293339
Copyright © 2018 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
In-Cooperation
- ISI: Information Sciences Institute
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 06 December 2018
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
FIRE'18
Acceptance Rates
Overall Acceptance Rate 19 of 64 submissions, 30%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 94Total Downloads
- Downloads (Last 12 months)6
- Downloads (Last 6 weeks)0
Reflects downloads up to 28 Jan 2025
Other Metrics
Citations
Cited By
View all- Pareed AIdicula S(2019)A Relation Extraction System for Indian LanguagesAdvances in Science, Technology and Engineering Systems Journal10.25046/aj0402084:2(65-69)Online publication date: 2019
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in