Results 241 to 250 of about 44,902,161 (285)

SHORT SCIENTIFIC TEXTS CLASSIFICATION

Научно-техническая информация. Серия 1: Организация и методика информационной работы, 2023
Представлен анализ реализаций методов векторизации текстовой информации; описаны выбор модели классификации научных трудов и обучение лингвистической модели BERT на домене научных текстов. Приведены результаты экспериментов по обучению моделей классификации научных статей по первому и второму уровням ГРНТИ.
openaire   +1 more source

From Text Classification to Keyphrase Extraction for Short Text

2019 IEEE International Conference on Big Data (Big Data), 2019
Existing keyphrase extraction approaches often suffer from issues such as the sparsity and brevity of short text (e.g., headlines, queries, and tweets). In this paper, we propose a novel keyphrase extraction method for short text by utilizing recurrent neural networks. The main idea behind our approach is to classify short text into a relevant class or
Song-Eun Lee, Kang-Min Kim, Woo-Jong Ryu, Jemin Park, SangKeun Lee 0001   +4 more
openaire   +2 more sources

Prompt-Learning for Short Text Classification

IEEE Transactions on Knowledge and Data Engineering
Jipeng Qiang, Xindong Wu, Yi Zhu
exaly   +3 more sources

Introducing Semantics in Short Text Classification

2018
To overcome short text classification issues due to shortness and sparseness, the enrichment process is classically proposed: topics (word clusters) are extracted from external knowledge sources using Latent Dirichlet Allocation. All the words, associated to topics which encompass short text words, are added to the initial short text content.
Ameni Bouaziz, Célia da Costa Pereira, Christel Dartigues-Pallez, Frédéric Precioso   +3 more
openaire   +2 more sources

Short Text Classification Based on Semantics

2015
Data sparseness and unseen words are two major problems in short text classification. In such a case, it is unsuitable to directly use the vector space model (VSM) which focuses on the statistical occurrence of the terms to represent the text. To solve these problems, we present a novel short text classification method based on semantics. The method of
Chenglong Ma, Xin Wan, Zhen Zhang, Taisong Li, Yan Zhang   +4 more
openaire   +2 more sources

Study on Short Text Classification with Integrated Algorithm

2016 13th Web Information Systems and Applications Conference (WISA), 2016
With the rapid growth of the number of short text, how to effectively realize the automatic classification of short text is needed to be solved in the information domain. According to the characteristics of short text, this paper proposes Bagging_NB & Bagging_BSJ, which are two classification algorithms based on the improvement of current integrated ...
Dexin Zhao, Nana Du, Liangliang Qin
openaire   +1 more source

A Convolutional Architecture for Short Text Expansion and Classification

2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015
In this paper, we propose a convolutional framework for short texts expansion and classification. Particularly, by using additive composition over word embeddings from context with variable window width, the representations of multi-scale semantic units are computed first.
Peng Wang 0079, Jiaming Xu 0001, Bo Xu 0002, Cheng-Lin Liu, Hongwei Hao   +4 more
openaire   +2 more sources

Wikipedia Based Short Text Classification Method

Lecture Notes in Computer Science, 2017
Short text is usually expressed in refined slightly, insufficient information, which makes text classification difficult. But we can try to introduce some information from the existing knowledge base to strengthen the performance of short text classification. Wikipedia [2, 13, 15] is now the largest human-edited knowledge base of high quality. It would
Yi Cai
exaly   +3 more sources

Short text classification by detecting information path

Proceedings of the 22nd ACM international conference on Information & Knowledge Management, 2013
Short text is becoming ubiquitous in many modern information systems. Due to the shortness and sparseness of short texts, there are less informative word co-occurrences among them, which naturally pose great difficulty for classification tasks on such data. To overcome this difficulty, this paper proposes a new way for effectively classifying the short
Shitao Zhang, Xiaoming Jin, Dou Shen, Bin Cao 0001, Xuetao Ding, Xiaochen Zhang   +5 more
openaire   +1 more source

Towards effective short text deep classification

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval, 2011
Recently, more and more short texts (e.g., ads, tweets) appear on the Web. Classifying short texts into a large taxonomy like ODP or Wikipedia category system has become an important mining task to improve the performance of many applications such as contextual advertising and topic detection for micro-blogging.
Xinruo Sun, Haofen Wang, Yong Yu 0001
openaire   +2 more sources