Results 11 to 20 of about 61,609 (261)
Proceedings of the International AAAI Conference on Web and Social Media, 2021 Managing large collections of documents is an important problem for many areas of science, industry, and culture. Probabilistic topic modeling offers a promising solution. Topic modeling is an unsupervised machine learning method that learns the underlying themes in a large collection of otherwise unorganized documents.
Allison June-Barlow Chaney +1 more
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Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022 We propose a new problem called coordinated topic modeling that imitates human behavior while describing a text corpus. It considers a set of well-defined topics like the axes of a semantic space with a reference representation. It then uses the axes to model a corpus for easily understandable representation. This new task helps represent a corpus more
Pritom Saha Akash +2 more
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CoRR, 2021 We propose an Exclusive Topic Modeling (ETM) for unsupervised text classification, which is able to 1) identify the field-specific keywords though less frequently appeared and 2) deliver well-structured topics with exclusive words. In particular, a weighted Lasso penalty is imposed to reduce the dominance of the frequently appearing yet less relevant ...
Hao Lei, Ying Chen
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Enhancing topic clustering for Arabic security news based on k‐means and topic modelling
IET Networks, 2021 The internet has become one of the main sources of news spread as it unleashed the information dissemination space, where the news websites express opinions on entities while also reporting on recent or unusual security risks.
Adel R. Alharbi +2 more
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, 2012 We introduce the topical relevance model (TRLM) as a generalization of the standard relevance model (RLM). The TRLM alleviates the limitations of the RLM by exploiting the multi-topical structure of pseudo-relevant documents. In TRLM, intra-topical document and query term co-occurrences are favoured, whereas the inter-topical ones are down-weighted ...
Ganguly, Debasis +2 more
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Conceptualization Topic Modeling [PDF]
CoRR, 2017 Recently, topic modeling has been widely used to discover the abstract topics in text corpora. Most of the existing topic models are based on the assumption of three-layer hierarchical Bayesian structure, i.e. each document is modeled as a probability distribution over topics, and each topic is a probability distribution over words.
Yi-Kun Tang +3 more
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The Evolution of Topic Modeling [PDF]
ACM Computing Surveys, 2022 Topic models have been applied to everything from books to newspapers to social media posts in an effort to identify the most prevalent themes of a text corpus. We provide an in-depth analysis of unsupervised topic models from their inception to today. We trace the origins of different types of contemporary topic models, beginning in the 1990s, and we ...
Rob Churchill, Lisa Singh
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Technology Project Summaries as a Predictor of Crowdfunding Success
Technology Innovation Management Review, 2022 Crowdfunding has emerged in recent years as an important alternative means for technology entrepreneurs to raise funds for their products and business ideas. While the success rate of crowdfunding projects is somewhat low, scholarly understanding of what
M. Westerlund +3 more
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TOPIC MODELLING SKRIPSI MENGGUNAKAN METODE LATENT DIRICLHET ALLOCATION
JSiI (Jurnal Sistem Informasi), 2020 Abstrak - Program Studi Sastra Inggris di Universitas Islam Negeri Sunan Ampel Surabaya (UINSA) telah ditemukan permasalahan bahwa belum ada yang melakukan clustering pada topik skripsi mahasiswa. Clustering tersebut digunakan dalam topic modelling untuk
Alif Iffan Alfanzar +2 more
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IEEE Access, 2023 The research interest of knowledge in human resource management (HRM) is significant. Bibliometric or systematic literature review studies capture the main areas and trends in the field of HRM. However, many HRM studies work only with a limited number of
Lukas Falat +3 more
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