Semantic Information Extraction: Overview and Basic Techniques
Semantic Information Extraction: Overview and Basic Techniques
Semantic Information Extraction: Overview and Basic Techniques
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<strong>Semantic</strong> IE: Summary<br />
• <strong>Semantic</strong> class mining<br />
Sample: {C++, C#, Java, PHP, Perl, …}<br />
Methods: Pattern matching (1st-order co-occurrences); distributional<br />
similarity (2nd-order co-occurrences)<br />
• <strong>Semantic</strong> hierarchy construction<br />
Key task: Hypernymy extraction (Beijingcity; pearfruit; pearshape)<br />
Pattern matching; tuple aggregation; Label voting<br />
• Mining attribute names <strong>and</strong> values<br />
Samples: (company, CEO); (China, capital, Beijing)<br />
Pattern learning; pattern matching; Table extraction; Wikipedia Infobox<br />
• General relation & event extraction<br />
Sample: WorkFor(Susan Dumais, Microsoft Research)<br />
Supervised, semi-supervised, & unsupervised learning<br />
Process contexts (especially middle contexts)
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