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Sudha Bhingardive

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AAAI Conference 2016 Conference Paper

WWDS APIs: Application Programming Interfaces for Efficient Manipulation of World WordNet Database Structure

Hanumant Redkar
Sudha Bhingardive
Kevin Patel
Pushpak Bhattacharyya
Neha Prabhugaonkar
Apurva Nagvenkar
Ramdas Karmali

WordNets are useful resources for natu processing. Various WordNets for different l been developed by different groups. Re WordNet Database Structure (WWDS) was Redkar et. al (2015) as a common platform different WordNets. However, it is underutiliz of programming interface. In this paper, we p APIs, which are designed to address this short WWDS APIs, in conjunction with WWDS, ac that enables developers to utilize Word worrying about the underlying storage struct are developed in PHP, Java, and Python, a preferred programming languages of most d researchers working in language technologie can help in various applications like machi word sense disambiguation, multilingual retrieval, etc.

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AAAI Conference 2015 Conference Paper

World WordNet Database Structure: An Efficient Schema for Storing Information of WordNets of the World

Hanumant Redkar
Sudha Bhingardive
Diptesh Kanojia
Pushpak Bhattacharyya

WordNet is an online lexical resource which expresses unique concepts in a language. English WordNet is the first WordNet which was developed at Princeton University. Over a period of time, many language WordNets were developed by various organizations all over the world. It has always been a challenge to store the WordNet data. Some WordNets are stored using file system and some WordNets are stored using different database models. In this paper, we present the World WordNet Database Structure which can be used to efficiently store the WordNet information of all languages of the World. This design can be adapted by most language WordNets to store information such as synset data, semantic and lexical relations, ontology details, language specific features, linguistic information, etc. An attempt is made to develop Application Programming Interfaces to manipulate the data from these databases. This database structure can help in various Natural Language Processing applications like Multilingual Information Retrieval, Word Sense Disambiguation, Machine Translation, etc.

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