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Semantic Title Evaluation and Recommendation Based on Topic Models

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Date

2013

Authors

Jin, Huidong (Warren)
Zhang, Lijiu
Du, Lan

Journal Title

Journal ISSN

Volume Title

Publisher

Springer

Abstract

To digest tremendous documents efficiently, people often resort to their titles, which normally provide a concise and semantic representation of main text. Some titles however are misleading due to lexical ambiguity or eye-catching intention. The requirem

Description

Keywords

Citation

URI

http://hdl.handle.net/1885/29233

Collections

ANU Research Publications

Source

Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2013 Workshops

Type

Conference paper

Book Title

Entity type

Access Statement

License Rights

DOI

10.1007/978-3-642-37456-2_34

Restricted until

2037-12-31

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01_Jin_Semantic_Title_Evaluation_and_2013.pdf (339.66 KB)

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