SQL Queries Over Unstructured Text Databases Export

@proceedings{citeulike:1907870, abstract = {Text documents often embed data that is structured in nature. By processing a text database with information extraction systems, we can define a variety of structured "relations" over which we can then issue SQL queries. Processing SQL queries in this text-based scenario presents multiple challenges. One key challenge is efficiency: information extraction is a time-consuming process, so query processing strategies should pick efficient extraction systems whenever possible, and also minimize the number of documents that they process. Another key challenge is result quality: extraction systems might output erroneous information or miss information that they should capture; also, efficiency-related query processing decisions (e.g., to avoid processing large numbers of useless documents) may compromise result completeness. To address these challenges, we characterize SQL query processing strategies in terms of their efficiency and result quality, and discuss the (user-specific) tradeoff between these two properties.}, author = {Jain, A. and Doan, A. and Gravano, L.}, booktitle = {Data Engineering, 2007. ICDE 2007. IEEE 23rd International Conference on}, citeulike-article-id = {1907870}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/ICDE.2007.368986}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4221776}, doi = {10.1109/ICDE.2007.368986}, journal = {Data Engineering, 2007. ICDE 2007. IEEE 23rd International Conference on}, keywords = {document, sql, text, unstructured}, pages = {1255--1257}, posted-at = {2007-11-13 16:18:42}, priority = {5}, title = {SQL Queries Over Unstructured Text Databases}, url = {http://dx.doi.org/10.1109/ICDE.2007.368986}, year = {2007} }

TY - CONF ID - citeulike:1907870 L3 - citeulike-article-id:1907870 N2 - Text documents often embed data that is structured in nature. By processing a text database with information extraction systems, we can define a variety of structured "relations" over which we can then issue SQL queries. Processing SQL queries in this text-based scenario presents multiple challenges. One key challenge is efficiency: information extraction is a time-consuming process, so query processing strategies should pick efficient extraction systems whenever possible, and also minimize the number of documents that they process. Another key challenge is result quality: extraction systems might output erroneous information or miss information that they should capture; also, efficiency-related query processing decisions (e.g., to avoid processing large numbers of useless documents) may compromise result completeness. To address these challenges, we characterize SQL query processing strategies in terms of their efficiency and result quality, and discuss the (user-specific) tradeoff between these two properties. JF - Data Engineering, 2007. ICDE 2007. IEEE 23rd International Conference on EP - 1257 TI - SQL Queries Over Unstructured Text Databases T2 - Data Engineering, 2007. ICDE 2007. IEEE 23rd International Conference on SP - 1255 KW - document KW - sql KW - text KW - unstructured AU - Jain, A AU - Doan, A AU - Gravano, L PY - 2007/// UR - http://dx.doi.org/10.1109/ICDE.2007.368986 ER -