Semantically-driven explanatory text mining: Beyond keywords

John Atkinson-Abutridy

doi:10.1007/978-3-540-30498-2_28

Semantically-driven explanatory text mining: Beyond keywords

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Resumen

In this paper, a new explanatory and high-level approach to knowledge discovery from texts is described which uses natural language techniques and and evolutionary computation based optimization to find novel patterns in textual information. In addition, some results showing the promise of the approach towards effective text mining when compared to human performance are briefly discussed.

Idioma original	Inglés
Páginas (desde-hasta)	275-285
Número de páginas	11
Publicación	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen	3315
DOI	https://doi.org/10.1007/978-3-540-30498-2_28
Estado	Publicada - 2004
Publicado de forma externa	Sí
Evento	9th Ibero-American Conference on AI: Advances in Artificial Intelligence- IBERAMIA 2004 - Puebla, México Duración: 22 nov. 2004 → 26 nov. 2004

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10.1007/978-3-540-30498-2_28

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title = "Semantically-driven explanatory text mining: Beyond keywords",

abstract = "In this paper, a new explanatory and high-level approach to knowledge discovery from texts is described which uses natural language techniques and and evolutionary computation based optimization to find novel patterns in textual information. In addition, some results showing the promise of the approach towards effective text mining when compared to human performance are briefly discussed.",

author = "John Atkinson-Abutridy",

year = "2004",

doi = "10.1007/978-3-540-30498-2_28",

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journal = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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AB - In this paper, a new explanatory and high-level approach to knowledge discovery from texts is described which uses natural language techniques and and evolutionary computation based optimization to find novel patterns in textual information. In addition, some results showing the promise of the approach towards effective text mining when compared to human performance are briefly discussed.

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DO - 10.1007/978-3-540-30498-2_28

M3 - Conference article

AN - SCOPUS:22944453072

SN - 0302-9743

VL - 3315

SP - 275

EP - 285

JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Y2 - 22 November 2004 through 26 November 2004

ER -

Semantically-driven explanatory text mining: Beyond keywords

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