MATEC Web Conf.
Volume 189, 20182018 2nd International Conference on Material Engineering and Advanced Manufacturing Technology (MEAMT 2018)
|Number of page(s)||7|
|Section||Cloud & Network|
|Published online||10 August 2018|
Research of specific field ultra-short text classification based on collaborative filtering algorithm
HeBei Aisino Technology Co., Ltd, Hebei, China
* Corresponding author: firstname.lastname@example.org
In some specific fields, there are a lot of ultra-short texts that need to be categorized. This paper proposes an ultra-short text classification method based on collaborative filtering algorithm aiming at the problems such as short text content, short length, sparse features, and large number of categories in certain fields. First, converting ultra-short text into word frequency vector by doing Chinese word segmentation and calculating word frequency; Secondly, combining relevant data in specific fields, defining the ultra-short texts as users, categories as items, and then constructing a user-item recommendation matrix. Finally, calculating text similarity by using cosine similarity method and obtaining the classification results. The experimental results show that the proposed method can well solve the problem of classification of ultra-short texts in specific fields, and the average accuracy is 9.19% and 3.81% higher than vector space model and topic similarity method respectively.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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