Results 11 to 20 of about 787,502 (308)
Short Text Understanding Combining Text Conceptualization and Transformer Embedding [PDF]
IEEE Access, 2019 Short text understanding is a key task and popular issue in current natural language processing. Because the content of short texts is characterized by sparsity and semantic limitation, the traditional search methods that analyze only the semantics of ...
Jun Li +3 more
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Using deep learning for short text understanding [PDF]
Journal of Big Data, 2017 Classifying short texts to one category or clustering semantically related texts is challenging, and the importance of both is growing due to the rise of microblogging platforms, digital news feeds, and the like.
Justin Zhan, Binay Dahal
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A New Method for Short Text Compression
IEEE Access, 2023 Short texts cannot be compressed effectively with general-purpose compression methods. Methods developed to compress short texts often use static dictionaries.
Murat Aslanyurek, Altan Mesut
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Measuring Short Text Reuse for the Urdu Language
IEEE Access, 2018 Text reuse occurs when one borrows the text (either verbatim or paraphrased) from an earlier written text. A large and increasing amount of digital text is easily and readily available, making it simpler to reuse but difficult to detect.
Sara Sameen +4 more
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A Pitman-Yor Process Self-Aggregated Topic Model for Short Texts of Social Media
IEEE Access, 2021 In recent years, with the rapid growth of social media, short texts have been very prevalent on the internet. Due to the limited length of each short text, word co-occurrence information in this type of documents is sparse.
Yue Niu, Hongjie Zhang, Jing Li
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Short Text Clustering with Transformers
Computational Linguistics and Intellectual Technologies, 2021 Recent techniques for the task of short text clustering often rely on word embeddings as a transfer learning component. This paper shows that sentence vector representations from Transformers in conjunction with different clustering methods can be successfully applied to address the task. Furthermore, we demonstrate that the algorithm of enhancement of
Mikhail S. Burtsev, Leonid Pugachev
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A Hybrid Model with New Word Weighting for Fast Filtering Spam Short Texts
Sensors, 2023 Short message services (SMS), microblogging tools, instant message apps, and commercial websites produce numerous short text messages every day. These short text messages are usually guaranteed to reach mass audience with low cost.
Tian Xia +3 more
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Review of Deep Learning for Short Text Sentiment Tendency Analysis
Jisuanji kexue yu tansuo, 2021 Short text sentiment tendency analysis is one of the key research issues in the field of natural language processing. Sentiment tendency analysis is a series of methods, techniques and tools used to detect the semantics of subjective inclination ...
TANG Lingyan, XIONG Congcong, WANG Yuan, ZHOU Yubo, ZHAO Zijian
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Short Text Sentiment Analysis Based on Multi-Channel CNN With Multi-Head Attention Mechanism
IEEE Access, 2021 In view of the limited text features of short texts, features of short texts should be mined from various angles, and multiple sentiment feature combinations should be used to learn the hidden sentiment information. A novel sentiment analysis model based
Yue Feng, Yan Cheng
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