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With the development of weblogs and social networks, many news providers share their news headlines on different websites and weblogs. One of the main text mining topics is how to classify news into different groups. This study aims to classify news into various groups so that users can identify the most popular news group in the desired country at any given time. Based on Term Frequency-Inverse Document...
While systematic reviews (SRs) are positioned as an essential element of modern evidence-based medical practice, the creation and update of these reviews is resource intensive. In this research, we propose to leverage advanced analytics techniques for automatically classifying articles for inclusion and exclusion for systematic review update. Specifically, we used the soft-margin Support Vector Machine...
Ontology learning aims to facilitate the construction of ontologies by decreasing the amount of effort required to produce an ontology for a new domain. However, there are few studies that attempt to automate the entire ontology learning process from the collection of domain-specific literature, to text mining to build new ontologies or enrich existing ones. In this paper, we present a complete framework...
Text categorization is an important research field within text mining. A document, actually, is often full of class-independent ??general?? words which many documents and classes share. These ??general?? words do harm to text categorization rather than contribute to the task. Inspired by human cognitive procedure in text classification task, we propose a novel approach called Class Core Extraction...
Ontology learning has become a major area of research whose goal is to facilitate the construction of ontologies by decreasing the amount of effort required to produce an ontology for a new domain. However, there are few studies that attempt to automate the entire ontology learning process from the collection of domain-specific literature, to text mining to build new ontologies or enrich existing...
Question classification (QC) plays a key role in automated question answering (QA) systems. In Chinese QC, for example, a question is analyzed and then labeled with the question type it belongs to and the expected answer type. In this paper, we propose a novel method of Chinese QC that integrates syntactic tags and semantic tags into an alignment-based approach. We adopt a template alignment (TA)...
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