A new vector representation of short texts for classification
Joint Authors
Source
The International Arab Journal of Information Technology
Issue
Vol. 17, Issue 2 (31 Mar. 2020), pp.241-249, 9 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2020-03-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Abstract EN
Short and sparse characteristics and synonyms and homonyms are main obstacles for short-text classification.
In recent years, research on short-text classification has focused on expanding short texts but has barely guaranteed the validity of expanded words.
This study proposes a new method to weaken these effects without external knowledge.
The proposed method analyses short texts by using the topic model based on Latent Dirichlet Allocation (LDA), represents each short text by using a vector space model and presents a new method to adjust the vector of short texts.
In the experiments, two open short-text data sets composed of google news and web search snippets are utilised to evaluate the classification performance and prove the effectiveness of our method.
American Psychological Association (APA)
Li, Yangyang& Liu, Bo. 2020. A new vector representation of short texts for classification. The International Arab Journal of Information Technology،Vol. 17, no. 2, pp.241-249.
https://search.emarefa.net/detail/BIM-954659
Modern Language Association (MLA)
Li, Yangyang& Liu, Bo. A new vector representation of short texts for classification. The International Arab Journal of Information Technology Vol. 17, no. 2 (Mar. 2020), pp.241-249.
https://search.emarefa.net/detail/BIM-954659
American Medical Association (AMA)
Li, Yangyang& Liu, Bo. A new vector representation of short texts for classification. The International Arab Journal of Information Technology. 2020. Vol. 17, no. 2, pp.241-249.
https://search.emarefa.net/detail/BIM-954659
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 248-249
Record ID
BIM-954659