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Hua et al., 2020 - Google Patents

Probabilistic topic modeling for comparative analysis of document collections

Hua et al., 2020

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Document ID
13609615273093164132
Author
Hua T
Lu C
Choo J
Reddy C
Publication year
Publication venue
ACM Transactions on Knowledge Discovery from Data (TKDD)

External Links

Snippet

Probabilistic topic models, which can discover hidden patterns in documents, have been extensively studied. However, rather than learning from a single document collection, numerous real-world applications demand a comprehensive understanding of the …
Continue reading at dl.acm.org (PDF) (other versions)

Classifications

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    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30705—Clustering or classification
    • G06F17/3071—Clustering or classification including class or cluster creation or modification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
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