A new vector representation of short texts for classification

Joint Authors

Liu, Bo
Li, Yangyang

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 Sciences and Information Technology

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