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Topic
Chinese Wiki-Based Word Sense Disambiguation
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Data
- Crawled from Wikipedia, cleaned and preprocessed by myself
- 164 words with # of fine-grained senses >=2
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Phrase list: https://gist.github.com/indiejoseph/eae09c673460aa0b56db
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The Experimented WSD Algorithms
(1) tfidf (inspired by https://www.itread01.com/hkyecfy.html)
(2) Lesk++ (inspired by Simple Embedding-Based Word Sense Disambiguation)
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Result
(1) tfidf
- Train: Test = 1:1, Total TestSize = 28,517 // No randomization
- Total Accuracy: 46.6% // Coarse-grained Accuracy
(2) Lesk++
- Train: Test = 7:3, Total TestSize = 8,576 // with randomization
- Total Accuracy: 59.34 % // Coarse-grained Accuracy
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Future Expectations
(1) cleaning and reviewing data manually
(2) extending dataset size
(3) application on WSD fine-grained task: named entity (exploiting features of Wikipedia)
Check doc for more details.