Mining Structures of Factual Knowledge from Text: An Effort-Light Approach (Synthesis Lectures on Data Mining and Knowledge Discovery)

by Xiang Ren and Jiawei Han

Jiawei Han, Lise Getoor, Wei Wang, Johannes Gehrke, and Robert Grossman

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Book cover for Mining Structures of Factual Knowledge from Text

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The real-world data, though massive, is largely unstructured, in the form of natural-language text. It is challenging but highly desirable to mine structures from massive text data, without extensive human annotation and labeling. In this book, we investigate the principles and methodologies of mining structures of factual knowledge (e.g., entities and their relationships) from massive, unstructured text corpora.

Departing from many existing structure extraction methods that have heavy reliance on human annotated data for model training, our effort-light approach leverages human-curated facts stored in external knowledge bases as distant supervision and exploits rich data redundancy in large text corpora for context understanding. This effort-light mining approach leads to a series of new principles and powerful methodologies for structuring text corpora, including (1) entity recognition, typing and synonym discovery, (2) entity relation extraction, and (3) open-domain attribute-value mining and information extraction. This book introduces this new research frontier and points out some promising research directions.
  • ISBN13 9781681733944
  • Publish Date 30 June 2018 (first published 26 June 2018)
  • Publish Status Active
  • Publish Country US
  • Imprint Morgan & Claypool Publishers
  • Format Hardcover
  • Pages 199
  • Language English