We present an approach to extract measured information from text (e.g., a 1370 • C melting point, a BMI greater than 29.9 kg/m 2 ). Such extractions are critically important across a wide range of domains -especially those involving search and exploration of scientific and technical documents. We first propose a rule-based entity extractor to mine measured quantities (i.e., a numeric value paired with a measurement unit), which supports a vast and comprehensive set of both common and obscure measurement units. Our method is highly robust and can correctly recover valid measured quantities even when significant errors are introduced through the process of converting document formats like PDF to plain text. Next, we describe an approach to extracting the properties being measured (e.g., the property pixel pitch in the phrase "a pixel pitch as high as 352 µm"). Finally, we present MQSearch: the realization of a search engine with full support for measured information.
Maiya et al. employed a rule-based approach to extract measured information from a text document, e.g., scientific and technical documents REF .
Mining Measured Information from Text
Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval
Computer Science