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Text Information Extraction and Aggregation in a Mobile-based Emergency Response System

机译:基于移动的应急系统中的文本信息提取与汇总

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A mobile-based emergency response system (MERS), as one of the important Mobile Government (m-Government) services, aims to reduce risks in an emergency situation. This paper describes an algorithm within MERS applications to automatically extract information from SMS data based on an ontology concept, a maximum entropy statistical model, and a set of fuzzy rules. The algorithm has four main functions: collect unstructured information from Short Message Service (SMS) emergency text message; conduct information extraction and aggregation including lexical analysis, name entity recognition, merging structure, and normalization and duplication; calculate similarity of SMS text messages; and generate query and results presentation.
机译:基于移动的紧急响应系统(MERS)作为重要的移动政府(m-Government)服务之一,旨在降低紧急情况下的风险。本文介绍了一种MERS应用程序中的算法,该算法基于本体概念,最大熵统计模型和一组模糊规则从SMS数据中自动提取信息。该算法具有四个主要功能:从短消息服务(SMS)紧急文本消息中收集非结构化信息;进行信息提取和汇总,包括词法分析,名称实体识别,合并结构以及标准化和重复;计算短信文本的相似度;并生成查询和结果表示。

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