Improving K Nearest Neighbor into String Vector Version for Text Categorization

Jo, Taeho

doi:10.23919/icact.2019.8702043

Cited by 21 publications

(56 citation statements)

References 7 publications

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“…It was proposed that words should be encoded into string vectors, in using the KNN algorithm for the word categorization [18]. Encoding words into string vectors was also proposed in using the KNN algorithm for extracting keywords [16]. It was proposed that texts should be encoded into string vectors, in using the KNN algorithm for the text categorization [17].…”

Section: B Word and Text Encodingmentioning

confidence: 99%

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String Vector based AHC Algorithm for Clustering Words Semantically

2024

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This article proposes the modified AHC (Agglomerative HierarchicalClustering) algorithm which clusters string vectors, instead ofnumerical vectors, as the approach to the word clustering. Theresults from applying the string vector based algorithms to the textclustering were successful in previous works and synergy effectbetween the text clustering and the word clustering is expected bycombining them with each other; the two facts become motivations forthis research. In this research, we define the operation on stringvectors called semantic similarity, and modify the AHC algorithm byadopting the proposed similarity metric as the approach to the wordclustering. The proposed AHC algorithm is empirically validated asthe better approach in clustering words in news articles andopinions. We need to define and characterize mathematically moreoperations on string vectors for modifying more advanced machinelearning algorithms.

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Section: B Word and Text Encodingmentioning

confidence: 99%

“…Encoding words into string vectors was also proposed in using the KNN algorithm for extracting keywords [16]. It was proposed that texts should be encoded into string vectors, in using the KNN algorithm for the text categorization [17]. The above literatures presented the previous cases of encoding raw data into string vectors.…”

Section: B Word and Text Encodingmentioning

confidence: 99%

String Vector based AHC Algorithm for Clustering Words Semantically

2024

Preprint

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“…The semantic similarity was applied for implementing the NTSO (Neural Text Self Organizer) which is the string vector based unsupervised neural networks, in 2010 [4]. It was applied for modifying the KNN algorithm into its string vector based version in 2018 [24]. In the above literatures, we present that the semantic similarity was defined as the base semantic operation on strings, and used for modifying the machine learning algorithms.…”

Section: B Semantic Operationsmentioning

confidence: 99%

Content based Word Clustering using Feature Similarity based AHC Algorithm

2024

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This article proposes the modified AHC (Agglomerative HierarchicalClustering) algorithm which considers the feature similarity and isapplied to the word clustering. The texts which are given asfeatures for encoding words into numerical vectors are semanticrelated entities, rather than independent ones, and the synergyeffect between the word clustering and the text clustering isexpected by combining both of them with each other. In thisresearch, we define the similarity metric between numerical vectorsconsidering the feature similarity, and modify the AHC algorithm byadopting the proposed similarity metric as the approach to the wordclustering. The proposed AHC algorithm is empirically validated asthe better approach in clustering words in news articles andopinions. The significance of this research is to improve theclustering performance by utilizing the feature similarities.

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“…Let us consider encoding words or texts into string vectors for modernizing the machine learning algorithms. Words were encoded into string vectors for applying the KNN algorithm to the word categorization [14]. Words were encoded into string vectors for applying the KNN algorithm for extracting keywords from a text [15].…”

Section: B Word and Text Encodingmentioning

confidence: 99%

Applying Table based AHC Algorithm to Semantic Word Clustering

2024

Preprint

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This article proposes the modified AHC (Agglomerative HierarchicalClustering) algorithm which clusters tables, instead of numericalvectors, as the approach to the word clustering. The motivations ofthis research are the successful results from applying the tablebased algorithms to the text clustering tasks in previous works andthe expectation of synergy effect between the text clustering andthe word clustering. In this research, we define the similaritymetric between tables representing words, and modify the AHCalgorithm by adopting the proposed similarity metric as the approachto the word clustering. The proposed AHC algorithm is empiricallyvalidated as the better approach in clustering words in newsarticles and opinions. In using the table based AHC algorithm, it iseasier to trace results from clustering words.

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Improving K Nearest Neighbor into String Vector Version for Text Categorization

Cited by 21 publications

References 7 publications

String Vector based AHC Algorithm for Clustering Words Semantically

String Vector based AHC Algorithm for Clustering Words Semantically

Content based Word Clustering using Feature Similarity based AHC Algorithm

Applying Table based AHC Algorithm to Semantic Word Clustering

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