Cross-Media Topic Mining on Wikipedia
Authors | Xikui Wang Yang Liu Donghui Wang Fei Wu |
|---|---|
Publication date | 2013 |
DOI | 10.1145/2502081.2502180 |
Links | Original |
Cross-Media Topic Mining on Wikipedia - scientific work related to Wikipedia quality published in 2013, written by Xikui Wang, Yang Liu, Donghui Wang and Fei Wu.
Overview
As a collaborative wiki-based encyclopedia, Wikipedia provides a huge amount of articles of various categories. In addition to their text corpus, Wikipedia also contains plenty of images which makes the articles more intuitive for readers to understand. To better organize these visual and textual data, one promising area of research is to jointly model the embedding topics across multi-modal data (i.e, cross-media ) from Wikipedia. In this work, authors propose to learn the projection matrices that map the data from heterogeneous feature spaces into a unified latent topic space. Different from previous approaches, by imposing the l 1 regularizers to the projection matrices, only a small number of relevant visual/textual words are associated with each topic, which makes model more interpretable and robust. Furthermore, the correlations of Wikipedia data in different modalities are explicitly considered in model. The effectiveness of the proposed topic extraction algorithm is verified by several experiments conducted on real Wikipedia datasets.
Embed
Wikipedia Quality
Wang, Xikui; Liu, Yang; Wang, Donghui; Wu, Fei. (2013). "[[Cross-Media Topic Mining on Wikipedia]]".DOI: 10.1145/2502081.2502180.
English Wikipedia
{{cite journal |last1=Wang |first1=Xikui |last2=Liu |first2=Yang |last3=Wang |first3=Donghui |last4=Wu |first4=Fei |title=Cross-Media Topic Mining on Wikipedia |date=2013 |doi=10.1145/2502081.2502180 |url=https://wikipediaquality.com/wiki/Cross-Media_Topic_Mining_on_Wikipedia}}
HTML
Wang, Xikui; Liu, Yang; Wang, Donghui; Wu, Fei. (2013). "<a href="https://wikipediaquality.com/wiki/Cross-Media_Topic_Mining_on_Wikipedia">Cross-Media Topic Mining on Wikipedia</a>".DOI: 10.1145/2502081.2502180.
