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Probst et al., 2007 - Google Patents

Semi-Supervised Learning of Attribute-Value Pairs from Product Descriptions.

Probst et al., 2007

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Document ID
11397789735116141751
Author
Probst K
Ghani R
Krema M
Fano A
Liu Y
Publication year
Publication venue
IJCAI

External Links

Snippet

We describe an approach to extract attribute-value pairs from product descriptions. This allows us to represent products as sets of such attribute-value pairs to augment product databases. Such a representation is useful for a variety of tasks where treating a product as …
Continue reading at citeseerx.ist.psu.edu (PDF) (other versions)

Classifications

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    • G06F17/30861—Retrieval from the Internet, e.g. browsers
    • G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
    • 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
    • G—PHYSICS
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    • G06Q10/00—Administration; Management

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