Automated Phrase Mining from Massive Text Corpora

Abstract

Web mining project report on Automated Phrase Mining from Massive Text Corpora  As one of the fundamental tasks in text analysis, phrase mining aims at extracting quality phrases from a text corpus and has various downstream applications including information extraction/retrieval, taxonomy construction, and topic modeling.

Most existing methods rely on complex, trained linguistic analyzers, and thus likely have unsatisfactory performance on text corpora of new domains and genres without extra but expensive adaption. None of the state-of-the-art models, even data-driven models, is fully automated because they require human experts for designing rules or labeling phrases.

Conclusion

In Web mining project report on Automated Phrase Mining from Massive Text Corpora  paper, we present an automated phrase mining framework with two novel techniques: the robust positive only distant training and the POS-guided phrasal segmentation incorporating part-of-speech (POS) tags, for the development of an automated phrase mining framework AutoPhrase.

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