Random-Walk-based Linguistic Sense Disambiguation Algorithm

A Random-Walk-based Linguistic Sense Disambiguation Algorithm is a Word Sense Disambiguation Algorithm that is based on a Random-Walk-based NLP Algorithm.

• Context:
  • It can range from being a Random-Walk-based Word Sense Disambiguation Algorithm to being an Random-Walk-based Sentence Sense Disambiguation Algorithm.
• Example(s):
  • Random-Walk-based sense disambiguation algorithm implemented by the ADW System (Pilehvar et al., 2013),
  • …
• Counter-Example(s):
  • Random-Walk-based Text Semantic Similarity Algorithm,
  • Alignment-based Linguistic Sense Disambiguation Algorithm.
• See: Word Sense, Semantic Similarity Measure, Semantic Word Similarity Measure, Semantic Word Similarity Benchmark Task.

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References

2013

• (Pilehvar et al., 2013) ⇒ Mohammad Taher Pilehvar, David Jurgens, and Roberto Navigli. (2013). “Align, Disambiguate and Walk: A Unified Approach for Measuring Semantic Similarity.” In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013) Volume 1: Long Papers.
  • QUOTE: Given a particular node (sense) in the network, repeated random walks beginning at that node will produce a frequency distribution over the nodes in the graph visited during the walk. To extend beyond a single sense, the random walk may be initialized and restarted from a set of senses (seed nodes), rather than just one; this multi-seed walk produces a multinomial distribution over all the senses in WordNet with higher probability assigned to senses that are frequently visited from the seeds.

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