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Izvorni znanstveni članak
https://doi.org/10.17559/TV-20190413112011

Hot Topic Discovery in Online Community using Topic Labels and Hot Features

Minjuan Zhong ; School of Information Technology and Management, Hunan University of Finance and Economics, Changsha, China

Puni tekst: engleski, pdf (431 KB) str. 1068-1075 preuzimanja: 362* citiraj
APA 6th Edition
Zhong, M. (2019). Hot Topic Discovery in Online Community using Topic Labels and Hot Features. Tehnički vjesnik, 26 (4), 1068-1075. https://doi.org/10.17559/TV-20190413112011
MLA 8th Edition
Zhong, Minjuan. "Hot Topic Discovery in Online Community using Topic Labels and Hot Features." Tehnički vjesnik, vol. 26, br. 4, 2019, str. 1068-1075. https://doi.org/10.17559/TV-20190413112011. Citirano 12.05.2021.
Chicago 17th Edition
Zhong, Minjuan. "Hot Topic Discovery in Online Community using Topic Labels and Hot Features." Tehnički vjesnik 26, br. 4 (2019): 1068-1075. https://doi.org/10.17559/TV-20190413112011
Harvard
Zhong, M. (2019). 'Hot Topic Discovery in Online Community using Topic Labels and Hot Features', Tehnički vjesnik, 26(4), str. 1068-1075. https://doi.org/10.17559/TV-20190413112011
Vancouver
Zhong M. Hot Topic Discovery in Online Community using Topic Labels and Hot Features. Tehnički vjesnik [Internet]. 2019 [pristupljeno 12.05.2021.];26(4):1068-1075. https://doi.org/10.17559/TV-20190413112011
IEEE
M. Zhong, "Hot Topic Discovery in Online Community using Topic Labels and Hot Features", Tehnički vjesnik, vol.26, br. 4, str. 1068-1075, 2019. [Online]. https://doi.org/10.17559/TV-20190413112011

Sažetak
With huge volumes of information on Internet, how to extract user-concerned hot topics quickly and effectively has become a fundamental task for information processing on Internet. Generally, hot topic detection includes two tasks, the first one is topic discovery and the other is its hotness evaluation. In this paper, we propose a hot topic detection method. For topic discovery, topics are identified by clustering based on extracted topic labels. For hotness evaluation, the proposed model has fully considered the internal and external dual features and combined them together. The experimental results over TianYa BBS demonstrate the efficiency of the proposed method: compared with topic discovery based on latent semantic indexing, the improved vector space model based on topic labels gets better results and the identified topics are more accurate. Moreover, the proposed hotness features could reflect the popularity of a topic, and hence have obtained better hot topic results finally.

Ključne riječi
external features; improved vector space model; internal features; topic hotness; topic label

Hrčak ID: 223303

URI
https://hrcak.srce.hr/223303

Posjeta: 595 *