Abstract
Acronym disambiguation is the process of linking an acronym in a given text to its intended expansion in the text. Acronyms are frequently used in short-texts such as news headlines and tweets. The direct application of state-of-art named entity disambiguation approaches on short text results in poor performance since, entities are not associated with their acronyms in the Knowledge Bases. Also, many acronyms in short-text represent out of Knowledge Base entities. Existing acronym dictionaries such as Acronymfinder also cannot be used for disambiguation as contextual information requires for disambiguation is absent in them. In this paper, we propose a system for effective disambiguation acronyms in short-text. In particular, we built an Acronym dictionary that is automatically updated with new acronyms by continuous monitoring of news media. Each acronym in our Acronym dictionary is enriched with additional meta information comprised of category, location and context words extracted from news articles. We use our enriched Acronym dictionary for disambiguation of acronyms in short-texts. Experimental results shows that our system is efficient in discovery and disambiguation of acronyms.
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Threshold is 0, 1 and 2 for acronyms with two letters, three letters and greater than three letters respectively.
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Narendra Modi, Smriti Irani, MS Dhoni, Arun Jaitely, Rahul Gandhi, Arvind Kejriwal and Ravishankar Prasad.
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Barua, J., Patel, D. (2016). Discovery, Enrichment and Disambiguation of Acronyms. In: Madria, S., Hara, T. (eds) Big Data Analytics and Knowledge Discovery. DaWaK 2016. Lecture Notes in Computer Science(), vol 9829. Springer, Cham. https://doi.org/10.1007/978-3-319-43946-4_23
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