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Reverse Dictionary Formation: State of the Art and Future Directions

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Abstract

In view of the limitation of the forward dictionaries to attend to the needs specific to the language producers, an alternate resource in the form of ‘Reverse Dictionary’ needs to be built. Reverse Dictionary aims to lexicalize the concept in the user’s mind by taking as input a natural language description of the concept and returning word/s that are in semantic correspondence to the description. A critical survey of the existing Reverse Dictionary works is presented in this paper. It is concluded that this problem has been addressed through five categories of approaches, namely, Information Retrieval-based approach, Graph-based approach, Mental dictionary-based approach, Vector Space Model-based approach, and Neural Language Model-based approach. We identify and highlight that the works reported so far do not account for human perceptions in the user input. However, as a NL is a system of perceptions and a Reverse Dictionary deals with natural language input, dealing with perception based information in the user input is important to capture his/her intent. To address the identified research gap, we have considered the concept of Precisiated Natural Language (PNL) based on Zadeh’s paradigm of Computational Theory of Perceptions. We have proposed to incorporate it into the traditional Information Retrieval (IR) architecture in building a Reverse Dictionary. To gain insights for the same, we have reported an experimental analysis of IR system based Wordster Reverse Dictionary.

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  1. Reddit: What’s the Word: https://www.reddit.com/r/whatstheword/, Words For That: http://www.wordsforthat.com/.

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  1. Bushra Siddique and M. M. Sufyan Beg have contributed equally to this work.

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  1. Department of Computer Engineering, Aligarh Muslim University, Aligarh, Uttar Pradesh, 202002, India

    Bushra Siddique & M. M. Sufyan Beg

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Siddique, B., Sufyan Beg, M.M. Reverse Dictionary Formation: State of the Art and Future Directions. SN COMPUT. SCI. 4, 168 (2023). https://doi.org/10.1007/s42979-022-01495-1

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