Abstract
While dictionaries suit to the needs of readers in finding the meanings of words, it falls short in addressing the needs of the language producers (writers/speakers) for getting an appropriate word corresponding to a concept in mind. ‘Reverse dictionary’ aim to address this problem. It takes a user description (in natural language) of the concept as input and provides a set of words satisfying that description as the output. The problem, although not novel, is of utmost concern in view of the compromises that generation of language producers have to make, the most common of all being the circumlocution. Ranging from books in printed form as earliest attempts to solve this problem, it is found to be addressed comprehensively in the literature only in the near past using diverse approaches based on Information Retrieval System, Mental Dictionary, Semantic Analysis and Neural Language Models. In order to carry out further research on this subject, a critical insight into the existing related works is vital which is provided in this paper. More importantly, identification of the research gaps followed by a discussion of possible enhancements of existing works and related lines of research is presented.
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Siddique, B., Sufyan Beg, M.M. (2019). A Review of Reverse Dictionary: Finding Words from Concept Description. In: Prateek, M., Sharma, D., Tiwari, R., Sharma, R., Kumar, K., Kumar, N. (eds) Next Generation Computing Technologies on Computational Intelligence. NGCT 2018. Communications in Computer and Information Science, vol 922. Springer, Singapore. https://doi.org/10.1007/978-981-15-1718-1_11
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