Scientific referential metadata creation with information retrieval and labeled topic modeling

Jia, Han; Liu, Xiaozhong

Permalink

https://hdl.handle.net/2142/36041 Copy

Description

Title

Scientific referential metadata creation with information retrieval and labeled topic modeling

Author(s)

• Jia, Han
• Liu, Xiaozhong

Issue Date

2013-02

Keyword(s)

• Metadata Generation
• Information Retrieval
• Referential Metadata
• Cyberlearning Resource
• User
• Scientific Publication
• Labeled Topic Modeling

Abstract

The goal of this research is to propose an innovative method of creating scientific referential metadata for a cyberinfrastructure-enabled learning environment to enhance learning experiences and to help students and scholars obtain better understanding of scientific publications. By using information retrieval, topic modeling, and meta-search approaches, different types of resources, such as related Wikipedia Pages, Datasets, Source Code, Video Lectures, Presentation Slides, and (online) Tutorials, for an assortment of publications and scientific (labeled) topics will be automatically retrieved, associated, and ranked. In order to test our method of automatic cyberlearning referential metadata generation, we designed a user experiment for the quality of the metadata for each scientific keyword and publication and resource ranking algorithms. Evaluation results based on MAP, MRR, and NDCG show that the cyberlearning referential metadata retrieved via meta-search and statistical relevance ranking can effectively help students better understand the essence of scientific keywords and publications.

Publisher

iSchools

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/36041

DOI

https://doi.org/10.9776/13192

Copyright and License Information

Copyright © 2013 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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