Discovering evolutionary theme patterns from text: an exploration of temporal text mining
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872 citations
Cites background or methods from "Discovering evolutionary theme patt..."
...A lot of previous work has shown the effectiveness of mixture of multinomial distributions (mixture language models) in extracting topics (themes, subtopics) from either plain text collections or contextualized collections [9, 1, 16, 15, 17, 12]....
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...No existing topic extraction work [9, 1, 16, 15, 17] could extract sentiment models from text, while no sentiment classification algorithm could model a mixture of topics simultaneously....
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...In this work, we present another approach to extract topic life cycles and sentiment dynamics, which is similar to the method used in [16]....
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...Following [9, 1, 16, 17], we further assume that there are k major topics (subtopics) in the documents, {θ1, θ2, ....
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...Definition 4 (Topic Life Cycle) A topic life cycle, also known as a theme life cycle in [16], is a time series representing the strength distribution of the neutral contents of a topic over the time line....
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434 citations
Cites background from "Discovering evolutionary theme patt..."
...Considering time information for the task of identifying and tracking topics in time-stamped text data is the focus of recent studies (e.g. [4, 7, 10, 11])....
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425 citations
Cites methods from "Discovering evolutionary theme patt..."
...[12] extracted latent themes from text and used the evolution graph of themes for temporal text mining....
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References
45,034 citations
"Discovering evolutionary theme patt..." refers methods in this paper
...To discover any evolutionary transition between two theme spans, we use the Kullback-Leibler divergence [4] to measure their evolution distance....
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30,570 citations
"Discovering evolutionary theme patt..." refers background or methods in this paper
...Using a word distribution to model topics is quite common in information retrieval and text mining [5, 9, 2]....
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...Specifically, the aspect models studied in [9, 20, 2] are related to the mixture theme model we use to extract themes....
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