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teaching:mfe:is [2015/04/13 14:45] svsummer [Design and Implementation of a Curriculum Revision Tool] |
teaching:mfe:is [2015/04/13 14:46] svsummer [Engineering a runtime system and compiler for AQL] |
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| ===== Engineering a runtime system and compiler for AQL ===== | ===== Engineering a runtime system and compiler for AQL ===== | ||
| - | Automatically extracting structured information from text is a task that has been pursued for decades. As a discipline, ///Information Extraction/// (IE) had its start with the [[http://acl.ldc.upenn.edu/C/C96/C96-1079.pdf|DARPA Message Understanding Conference in 1987]]. While early work in the area focused largely on military applications, recent changes have made information extraction increasingly important to an increasingly broad audience. Trends such as the rise of social media have produced huge amounts of text data, while analytics platforms like Hadoop have at the same time made the analysis of this data more accessible to a broad range of users. Since most analytics over text involves information extraction as a first step, IE is a very important part of data analysis in the enterprise today. | + | Automatically extracting structured information from text is a task that has been pursued for decades.Since most analytics over text involves information extraction as a first step, IE is a very important part of data analysis in the enterprise today. |
| In 2005, researchers at the IBM Almaden Research Center developped a new system specifically geared for practical information extraction in the enterprise. This effort lead to SystemT, a rule-based IE system with an SQL-like declarative language named AQL (Annotation Query Language). The declarative nature of AQL enables new kinds of tools for extractor development, and draws upon known techniques form query processing in relational database management systems to offer a cost-based optimizer that ensures high-througput performance. Recent research into the foundations of AQL (http://researcher.watson.ibm.com/researcher/files/us-fagin/jacm15.pdf) has shown that, as an alternative, it is also possible to build a runtime system for AQL based on special kinds of finite state automata. A potential benefit of this alternate runtime system is that text files need only be processed once (instead of multiple times in the cost-based optimizer backend) and may hence provide greater throughput. On the other hand, the alternate system can sometimes have larger memory requirements than the cost-based optimizer backend. | In 2005, researchers at the IBM Almaden Research Center developped a new system specifically geared for practical information extraction in the enterprise. This effort lead to SystemT, a rule-based IE system with an SQL-like declarative language named AQL (Annotation Query Language). The declarative nature of AQL enables new kinds of tools for extractor development, and draws upon known techniques form query processing in relational database management systems to offer a cost-based optimizer that ensures high-througput performance. Recent research into the foundations of AQL (http://researcher.watson.ibm.com/researcher/files/us-fagin/jacm15.pdf) has shown that, as an alternative, it is also possible to build a runtime system for AQL based on special kinds of finite state automata. A potential benefit of this alternate runtime system is that text files need only be processed once (instead of multiple times in the cost-based optimizer backend) and may hence provide greater throughput. On the other hand, the alternate system can sometimes have larger memory requirements than the cost-based optimizer backend. | ||