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• W2015536647 abstract "Automatic definition extraction has attracted wide interest in NLP domain and knowledge-based applications. One primary task of definition extraction is mining patterns from definitional sentences. Existing extraction methods of definitional patterns, either focus on manual extraction by intuition or observation, or aim to mine intricate definitional patterns by automatic extraction methods. The manual method requires large human resources to identify definitional patterns because of diverse lexico-syntactic structures. It inevitable suffers poor behavior especially extraction from cross-domain corpora. The latter method mainly considers precision in definition extraction, which is at cost of decreasing recall of definitions. Both of them are unsuitable for cross-domain definition extraction. To address those issues, this paper proposes a solution to perform automatic extraction of definitional patterns from multi-domain definitional sentences of Wikipedia. Our method FIND-SS is modified based on FIND-S algorithm and solves definition extraction problems of cross-domain corpora. Find-SS adopts a the more similar higher priority scheme to improve learning performance. It can accommodate some noisy information and does not require any pattern seeds for pattern learning. The experimental results indicate that our scenario is significantly superior to previous method." @default.
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• W2015536647 date "2014-12-01" @default.
• W2015536647 modified "2023-10-15" @default.
• W2015536647 title "Automatic Learning Common Definitional Patterns from Multi-domain Wikipedia Pages" @default.
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• W2015536647 doi "https://doi.org/10.1109/icdmw.2014.107" @default.
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