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- W2372990717 abstract "A novel clustering algorithm named TrigSigs was proposed to overcome the problem of record linkage models for unstructured data from network.It focuses on mining the associations of hidden attributes as the signatures of objects in unstructured data by trigger-pair model.It can group tokens which help identify objects and filter out noise.Then it assigns weight to tokens properly which makes feature vectors more representative for identifying objects.After these steps,it gains fine-grained object-based clustering result from unstructured data.Experiments on real datasets show that this algorithm can filter out most noise and assign weight for features properly,and improves the clustering results greatly." @default.
- W2372990717 created "2016-06-24" @default.
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- W2372990717 date "2010-12-01" @default.
- W2372990717 modified "2023-09-24" @default.
- W2372990717 title "TrigSigs: an effective record linkage algorithm for unstructured data" @default.
- W2372990717 doi "https://doi.org/10.3785/j.issn.1008-973x.2010.12.009" @default.
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