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Published in 2019 at "Journal of Classification"
DOI: 10.1007/s00357-018-9283-9
Abstract: The vector representation is one of the important parts in document clustering or classification, which can quantify the text. In this paper, a novel Cooccurrence Latent Semantic Vector Space Model (CLSVSM) is presented and the…
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Keywords:
latent semantic;
model;
occurrence;
vector space ... See more keywords
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Published in 2020 at "Communication Methods and Measures"
DOI: 10.1080/19312458.2020.1832976
Abstract: ABSTRACT Many social scientists recognize that quantitative text analysis is a useful research methodology, but its application is still concentrated in documents written in European languages, especially English, and few sub-fields of political science, such…
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Keywords:
seed;
analysis;
latent semantic;
domains languages ... See more keywords
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Published in 2018 at "Social Science Quarterly"
DOI: 10.1111/ssqu.12528
Abstract: Objective Topic modeling (TM) refers to a group of methods for mathematically identifying latent topics in large corpora of data. Although TM shows promise as a tool for social science research, most researchers lack awareness…
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Keywords:
semantic analysis;
modeling latent;
latent semantic;
topic modeling ... See more keywords
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Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/6781043
Abstract: Latent semantic analysis (LSA) is a natural language statistical model, which is considered as a method to acquire, generalize, and represent knowledge. Compared with other retrieval models based on concept dictionaries or concept networks, the…
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Keywords:
system;
latent semantic;
knowledge graph;
retrieval ... See more keywords