Constructing Concept Space from Social Collaborative Editing
Date Issued
2014
Date
2014
Author(s)
HSIEH, WEN-TAI
Abstract
With the prevalence of Social Networking Services (SNS), real-world consumption behaviors are influenced from reality to social networks. In order to utilize the information from social network, we need a concept space that can alter with application domain. In the presence of new vocabulary and continuously growing, and automatic ontology construction has been an important issue. There are previous studies concerning free-format ontology construction, enriching given ontologies from web or corpus sources, and construction of ontology from semi-structural corpora; among these studies, semi-structural corpora have been prevailing studies. In this thesis, we developed an adaptive framework for cross corpora on social collaborative editing, and we focus on semi-structural text mining in particular. The framework involves detection of named entity in a document, filtering of named entity, disambiguation detection, named entity expansion and ranking of the related named entity. We describe how this framework in detail and proposed method for each stage, and the metrics in the previous studies and the one we used for evaluation. We then discuss the evolution and quality of concept space. Our proposed framework made real-world corpora computationally possible, and a dynamic concept space is generated from this framework. It could deal with more diverse domains and languages, and for pragmatic real-world applications, our method shows better flexibility than previous studies.
Subjects
Concept Space
Automatic Ontology Construction
Social Collaborative Editing
Type
thesis