Results 11 to 20 of about 810,432 (208)
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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Micro-blog topic detection algorithm based on topic model
网络与信息安全学报, 2016 Micro-blog data has the characteristic of real-time,volume,short-text,and noise-rich.So it is a challenge for the traditional topic detection technology.A novel micro-blog topic detection algorithm based on topic model was proposed.Firstly,the micro-blog
Hua-jun HUANG +2 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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Zhishi guanli luntan, 2020 [Purpose/significance] This paper comprehensively summarizes the application of topic models in public policy texts, which helps researchers learn from existing research results and provides theoretical and practical support
Long Yixuan , Yi Huifang
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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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A Cross-Platform Personalized Recommender System for Connecting E-Commerce and Social Network
Future Internet, 2022 In this paper, we build a recommender system for a new study area: social commerce, which combines rich information about social network users and products on an e-commerce platform.
Jiaxu Zhao +3 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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Semantic Recognition of Ship Motion Patterns Entering and Leaving Port Based on Topic Model
Journal of Marine Science and Engineering, 2022 Recognition and understanding of ship motion patterns have excellent application value for ship navigation and maritime supervision, i.e., route planning and maritime risk assessment.
Gaocai Li +5 more
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A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts
Frontiers in Sociology, 2022 The richness of social media data has opened a new avenue for social science research to gain insights into human behaviors and experiences. In particular, emerging data-driven approaches relying on topic models provide entirely new perspectives on ...
Roman Egger, Joanne Yu
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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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