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Developing Automatic-Labeled Topic Modeling Based on SAO Structure for Technology Analysis. [PDF]
PLoS ONETopic modeling has become essential for identifying emerging technology trends, detecting technological concepts, and forecasting advancements. This study introduces a subject-action-object (SAO) based approach to overcome the limitations of existing ...
Minyoung Park, Sunhye Kim, Byungun Yoon
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Opportunities and challenges of proximity labeling for microbe-host cell interactions in tumor microenvironment [PDF]
Frontiers in Cellular and Infection MicrobiologyIn the tumor immune microenvironment, microbes promote tumor progression and metastasis by invading host cancer cells. Blocking these interactions is expected to provide new strategies for inhibiting tumor progression and metastasis, as well as opening ...
Shuang Qiu +9 more
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Systematic Literature Review of Topic Labeling
IEEE AccessThe rapid growth of textual data on the web has led researchers to develop methods in Natural Language Processing (NLP) to process, understand, and identify topics.
Salma Mekaoui +3 more
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Survey of Automatic Labeling Methods for Topic Models [PDF]
Jisuanji kexue yu tansuo, 2023 Topic models are often used in modeling unstructured corpora and discrete data to extract the latent topic. As topics are generally expressed in the form of word lists, it is usually difficult for users to understand the meanings of topics, especially ...
HE Dongbin, TAO Sha, ZHU Yanhong, REN Yanzhao, CHU Yunxia
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Survey on Pseudo-Labeling Methods in Deep Semi-supervised Learning [PDF]
Jisuanji kexue yu tansuo, 2022 With the development of intelligent technology, deep learning has become a hot topic in machine learning. It is playing a more and more important role in various fields.
LIU Yafen, ZHENG Yifeng, JIANG Lingyi, LI Guohe, ZHANG Wenjie
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Automatic Generation of Topic Labels [PDF]
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020 Topic modelling is a popular unsupervised method for identifying the underlying themes in document collections that has many applications in information retrieval. A topic is usually represented by a list of terms ranked by their probability but, since these can be difficult to interpret, various approaches have been developed to assign descriptive ...
Alokaili, A., Aletras, N., Stevenson, M.
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Advanced Hierarchical Topic Labeling for Short Text
IEEE Access, 2023 Hierarchical Topic Modeling is the probabilistic approach for discovering latent topics distributed hierarchically among the documents. The distributed topics are represented with the respective topic terms.
Paras Tiwari +3 more
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TLATR: Automatic Topic Labeling Using Automatic (Domain-Specific) Term Recognition
IEEE Access, 2021 Topic modeling is a probabilistic graphical model for discovering latent topics in text corpora by using multinomial distributions of topics over words. Topic labeling is used to assign meaningful labels for the discovered topics.
Ciprian-Octavian Truica +1 more
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Topic Model Recommendation Algorithm Combining Social Relationship and Time Factors [PDF]
Jisuanji gongcheng, 2020 The user behavior preference is often affected by many factors such as social relationships,time and so on.However,when constructing the user preference model,if only one single factor is considered,the model can be one-sided,resulting in incorrect ...
GAO Maoting, WANG Ji
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Zero-Shot Topic Labeling for Hazard Classification
Information, 2022 Topic classification is the task of mapping text onto a set of meaningful labels known beforehand. This scenario is very common both in academia and industry whenever there is the need of categorizing a big corpus of documents according to set custom ...
Andrea Rondinelli +2 more
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