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Named Entity Recognition in Hindi using Maximum Entropy and Transliteration

Sujan Kumar Saha, Partha Sarathi Ghosh, Sudeshna Sarkar, Pabitra Mitra
2008 POLIBITS Research Journal on Computer Science and Computer Engineering With Applications  
Proper transliteration makes the English lists useful in the NER tasks for such languages. In this paper, we have described a Maximum Entropy based NER system for Hindi.  ...  Index Terms-Gazetteer list preparation, named entity recognition, natural language processing, transliteration. http://hiren.info/indian-baby-names  ...  Then two-Sujan Kumar Saha, Partha Sarathi Ghosh, Sudeshna Sarkar, and Pabitra Mitra Named Entity Recognition in Hindi using Maximum Entropy and Transliteration N phase transliteration system is discussed  ... 
doi:10.17562/pb-38-4 fatcat:ewq4jxuf6vfitmgrpvzmsmbtwy

A Hybrid Feature Set based Maximum Entropy Hindi Named Entity Recognition

Sujan Kumar Saha, Sudeshna Sarkar, Pabitra Mitra
2008 International Joint Conference on Natural Language Processing  
We describe our effort in developing a Named Entity Recognition (NER) system for Hindi using Maximum Entropy (Max-Ent) approach. We developed a NER annotated corpora for the purpose.  ...  We have tried to identify the most relevant features for Hindi NER task to enable us to develop an efficient NER from the limited corpora developed.  ...  Introduction Named Entity Recognition involves locating and classifying the names in text.  ... 
dblp:conf/ijcnlp/SahaSM08 fatcat:6fqbck7ppfebfo2sna2wdrt7xa

Named-Entity Recognition for Hindi language using context pattern-based maximum entropy

Arti Jain, Divakar Yadav, Anuja Arora, Devendra K. Tayal
2022 Computer Science  
This paper describes a named-entity-recognition (NER) system for the Hindi language that uses two methodologies: an existing baseline maximum entropybased named-entity (BL-MENE) model, and the proposed  ...  BL-MENE utilizes several baseline features for the NER task but suffers from inaccurate named-entity (NE) boundary detection, misclassification errors, and the partial recognition of NEs due to certain  ...  Related Literature This section briefly discusses the literature that is related to the maximum entropy (ME) model and named-entity recognition in the Hindi language.  ... 
doi:10.7494/csci.2022.23.1.3977 dblp:journals/aghcs/JainYAT22 fatcat:adoua7vfubbzzom7rppomanfla

Name Entity Recognition by New Framework Using Machine Learning Algorithm

Daljit Kaur, Ashish Verma
2014 IOSR Journal of Computer Engineering  
These names are called Named Entities (NE) and Named Entity Recognition (NER), one of the main tasks of IE systems, seeks to locate and classify automatically these names into predefined categories.  ...  Our approach makes use of English contextual and morphological information to extract named entities. The context is represented by means of words that are used as clues for each named entity type.  ...  In this approach, they show machine transliteration of name entities for Hindi-English language using CRF as statistical probability tool. The accuracy of this system is 85.79%.  ... 
doi:10.9790/0661-16546671 fatcat:z2if4lmy6val3f7d4q6fin32s4

COMPARATIVE ANALYSIS OF VARIOUS APPROACHES BASED ON NAMED ENTITY RECOGNITION-A SURVEY

Sakshi .
2018 International Journal of Advanced Research in Computer Science  
Named Entity Recognition (NER) is the part of Information Extraction which is used to extract important information from the code-mixed and informal data and then classifies these extracting named entities  ...  This paper provides a survey of various methods and techniques which are being used in the extraction of proper nouns appeared in the document.  ...  Syllabification is used in the further process of named entity transliteration.  ... 
doi:10.26483/ijarcs.v9i3.6093 fatcat:dul72z4x3rgmngtsmy4vjourny

Hybrid Approach to English-Hindi Name Entity Transliteration [article]

Shruti Mathur, Varun Prakash Saxena
2014 arXiv   pre-print
Machine translation (MT) research in Indian languages is still in its infancy. Not much work has been done in proper transliteration of name entities in this domain.  ...  In this paper we address this issue. We have used English-Hindi language pair for our experiments and have used a hybrid approach.  ...  They used a maximum entropy based approach to train a classifier on pronunciation similarity, bilingual context and co-occurrence.  ... 
arXiv:1403.7455v1 fatcat:bwlvusin3raepoeio2onjsvwla

Improving the Quality of English-Hindi Name Entity Translation

Shruti Mathur, Varun Prakash Saxena
2014 International Journal of Computer Applications  
In the context of English-Hindi language pair, due to bad name entity translations, the quality of translation deteriorates.  ...  We need to devise mechanism and address this problem in a multi pronged approach.  ...  They used a maximum entropy based approach to train a classifier on pronunciation similarity, bilingual context and co-occurrence.  ... 
doi:10.5120/16954-7062 fatcat:acybjqub5resxm6s7e2uj7xovm

A comprehensive survey on Indian regional language processing

B. S. Harish, R. Kasturi Rangan
2020 SN Applied Sciences  
The tasks like machine translation, Named Entity Recognition, Sentiment Analysis and Parts-Of-Speech tagging are reviewed with respect to Rule, Statistical and Neural based approaches.  ...  In recent information explosion, contents in internet are multilingual and majority will be in the form of natural languages.  ...  Named Entity Recognition (NER) task performs better in statistical approach.  ... 
doi:10.1007/s42452-020-2983-x fatcat:e3u5r5qo7ngapj5mbiwit7qlwi

Named Entity Recognition [chapter]

Frédéric Béchet
2011 Spoken Language Understanding  
Named Entity Recognition(NER) is the process of identifying and classifying all proper noun into pre-defined classes such as persons, locations, organization and others.  ...  We also describe the different approaches used in NER and also the work in NER in different Indian languages like Bengali, Telugu, Hindi, Oriya and Urdu along with the methodologies used.  ...  Two-phase transliteration methodology was used to make the English lists useful in the Hindi NER task.  ... 
doi:10.1002/9781119992691.ch10 fatcat:pleazbt7mna6vnxxlcuhovvwwq

Challenges of Urdu Named Entity Recognition: A Scarce Resourced Languageq

Saeeda Naz, Arif Iqbal Umar, Syed Hamad Shirazi, Sajjad Ahmad Khan, Imtiaz Ahmed, Akbar Ali Khan
2014 Research Journal of Applied Sciences Engineering and Technology  
hindi named entity recognition using conditional Named entity recognition in Hindi using maximum random fields and feature induction.  ...  A hybrid named feature set based maximum entropy Hindi named entity recognition system for south Asian entity recognition.  ... 
doi:10.19026/rjaset.8.1095 fatcat:vfpo23flv5glpfd3w2dkxzoyii

DETECTION AND CATEGORIZATION OF NAMED ENTITIES IN INDIAN LANGUAGES USING HIDDEN MARKOV MODEL

Deepti Chopra, Sudha Morwal
2013 Zenodo  
Named Entity Recognition (NER) is the task in which proper nouns in a given document are discovered and then categorized into respective classes.  ...  In this paper, we have tried to explain NER, different approaches of NER and finally some results of NER in natural languages. KEYWORDS HMM; NER; Performance Metrics; Accuracy  ...  [12] Maximum Entropy Markov Model (MEMM) It involves combination of both the theories of Hidden Markov Model as well as Maximum Entropy Model.  ... 
doi:10.5281/zenodo.3653706 fatcat:gwrtbxgxyngqflowwtuw4n5inq

Survey of Named Entity Recognition Techniques for Various Indian Regional Languages

Shrutika Kale, Sharvari Govilkar
2017 International Journal of Computer Applications  
Named entity recognition is also called as entity chunking, entity identification and entity extraction.  ...  Named entity recognition is a process and study of identification of entities that are proper nouns and classifying them to their appropriate pre-defined class, also called as tag.  ...  described a Maximum Entropy based NER system for Hindi.  ... 
doi:10.5120/ijca2017913621 fatcat:cdy2fxldgrewzciwpwxm2yy7ri

A Semi-supervised Approach for Maximum Entropy Based Hindi Named Entity Recognition [chapter]

Sujan Kumar Saha, Pabitra Mitra, Sudeshna Sarkar
2009 Lecture Notes in Computer Science  
We use a semi-supervised approach which uses a small annotated corpus and a large raw corpus for the Hindi NER task using maximum entropy classifier.  ...  Scarcity of annotated data is a challenge in building high performance named entity recognition (NER) systems in resource poor languages.  ...  In this paper we propose a semi-supervised approach to named entity recognition and applied it on the Hindi NER task.  ... 
doi:10.1007/978-3-642-11164-8_36 fatcat:vcs2uu2kt5c7xew2qckaz2hdkm

A Survey on Various Approach used in Named Entity Recognition for Indian Languages

Dikshan N., Harshad Bhadka
2017 International Journal of Computer Applications  
many more. [9] By using two machine learning approach in their paper as Hidden Markov Model and Entropy Markov Model for Punjabi named entity recognition, they have focused on general challenges  ...  And they used Standford's NER tool for name entity recognition. Out of total name entities of 9234, 9180 entities were generated from the system.  ... 
doi:10.5120/ijca2017913878 fatcat:rda4faeyyrhrnngxiyvvpn44o4

Maximum Entropy Approach based Named Entity Recognition in Punjabi Language

Arshdeep Singh, Jyoti Rani, Amandeep Kaur
2013 International Journal of Computer Applications  
This work reports about the evaluation of a Named Entity Recognition (NER) system for Punjabi language using the Maximum Entropy Approach (MAXENT).  ...  Named Entity Recognition is the task of identifying and classifying named entities into some predefine categories like person, location, organization etc.  ...  We have evaluated a Maximum Entropy Markov Model, a machine learning approach for named entity recognition in punjabi language and identified suitable features for this NER task.  ... 
doi:10.5120/14553-2650 fatcat:ouzsqoirf5fxrcxakxxm45wp4e
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