Using Soft-Matching Mined Rules to Improve Information Extraction
نویسندگان
چکیده
By discovering predictive relationships between different pieces of extracted data, data-mining algorithms can be used to improve the accuracy of information extraction. However, textual variation due to typos, abbreviations, and other sources can prevent the productive discovery and utilization of hard-matching rules. Recent methods for inducing softmatching rules from extracted data can more effectively find and exploit predictive relationships in textual data. This paper presents techniques for using mined soft-matching association rules to increase the accuracy of information extraction. Experimental results on a corpus of computer-science job postings demonstrate that soft-matching rules improve information extraction more effectively than hard-matching rules.
منابع مشابه
Text Mining with Information Extraction
The popularity of the Web and the large number of documents available in electronic form has motivated the search for hidden knowledge in text collections. Consequently, there is growing research interest in the general topic of text mining. In this paper, we develop a text-mining system by integrating methods from Information Extraction (IE) and Data Mining (Knowledge Discovery from Databases ...
متن کاملCascading Use of Soft and Hard Matching Pattern Rules for Weakly Supervised Information Extraction
Current rule induction techniques based on hard matching (i.e., strict slot-by-slot matching) tend to fare poorly in extracting information from natural language texts, which often exhibit great variations. The reason is that hard matching techniques result in relatively high precision but low recall. To tackle this problem, we take advantage of the newly proposed soft pattern rules which offer...
متن کاملA Local Tree Alignment-based Soft Pattern Matching Approach for Information Extraction
This paper presents a new soft pattern matching method which aims to improve the recall with minimized precision loss in information extraction tasks. Our approach is based on a local tree alignment algorithm, and an effective strategy for controlling flexibility of the pattern matching will be presented. The experimental results show that the method can significantly improve the information ex...
متن کاملA Mutually Beneficial Integration of Data Mining and Information Extraction
Text mining concerns applying data mining techniques to unstructured text. Information extraction (IE) is a form of shallow text understanding that locates specific pieces of data in natural language documents, transforming unstructured text into a structured database. This paper describes a system called DISCOTEX, that combines IE and data mining methodologies to perform text mining as well as...
متن کاملUsing a Data Mining Tool and FP-Growth Algorithm Application for Extraction of the Rules in two Different Dataset (TECHNICAL NOTE)
In this paper, we want to improve association rules in order to be used in recommenders. Recommender systems present a method to create the personalized offers. One of the most important types of recommender systems is the collaborative filtering that deals with data mining in user information and offering them the appropriate item. Among the data mining methods, finding frequent item sets and ...
متن کامل