Development of a Micro Hindi Opinion WordNet and Aligning with Hown Ontology for Automatic Recognition of Opinion Words from Hindi Documents

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 827)


The Indian languages are deprived in terms of accessibility of natural language tools. Especially, the tools for carrying out the particular opinion mining task: opinion word orientation in native language is not available. Reasoning about such natural language words requires a semantically rich lexical resource. When the ontology is aligned with a lexical resource like WordNet, a rich knowledge base is created which can be useful for various information retrieval and natural language processing applications. In order to do this, a micro level Hindi Opinion WordNet is developed and is aligned with the Hindi Opinion WordNet Ontology (HOWN). The opinion lexicon (both Hindi positive and negative words) for 700 Hindi adjectives is also developed. The synset ID values of Hindi opinion synsets are mapped with the synset ID values of corresponding English opinion WordNet synsets. A front end query interface is designed to query the HOWN ontology for opinion word details. This query is transformed into SPARQL format. This task is for automatic recognition of opinionated terms from Hindi documents by the machine.


Semantic web Ontology Hindi WordNet Opinion words SPARQL 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.GITAM (Deemed to be University)HyderabadIndia
  2. 2.New York UniversityBrooklynUSA
  3. 3.Rochester Institute of TechnologyRochesterUSA

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