An Algebraic Approach to Rule-Based Information Extraction

Traditional approaches to rule-based information extraction (IE) have primarily been based on regular expression grammars. However, these grammar-based systems have difficulty scaling to large data sets and large numbers of rules. Inspired by traditional database research, we propose an algebraic approach to rule-based IE that addresses these scalability issues through query optimization. The operators of our algebra are motivated by our experience in building several rule-based extraction programs over diverse data sets. We present the operators of our algebra and propose several optimization strategies motivated by the text-specific characteristics of our operators. Finally we validate the potential benefits of our approach by extensive experiments over real-world blog data.

• Type: Conference
• Year: 2008
• Where: ICDE
• Authors: Frederick Reiss, Sriram Raghavan, Rajasekar Krishnamurthy, Huaiyu Zhu, Shivakumar Vaithyanathan
• Keywords: Database, ICDE 2008, Rule-based Extraction Programs, Rule-based Ie, Rule-based Information Extraction