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100%: Zapf, Laura: How Did English Songs Evolve? Retrieving Information from Song Lyrics Via Natural Language Processing and Statistical Topic Modeling (ISBN: 9783346376251) in Englisch, Taschenbuch.Nur diese Ausgabe anzeigen…
100%: Zapf, Laura: How Did English Songs Evolve? Retrieving Information from Song Lyrics Via Natural Language Processing and Statistical Topic Modeling (eBook, PDF) (ISBN: 9783346376244) 2019, in Englisch, auch als eBook.Nur diese Ausgabe anzeigen…
How Did English Songs Evolve? Retrieving Information from Song Lyrics Via Natural Language Processing and Statistical Topic Modeling
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Bester Preis: Fr. 44.03 (€ 44.99)¹ (vom 02.07.2021)1
How Did English Songs Evolve? Retrieving Information from Song Lyrics Via Natural Language Processing and Statistical Topic Modeling (2021)
~EN PB NWISBN: 9783346376251 bzw. 3346376257, vermutlich in Englisch, GRIN Verlag, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
Druck auf Anfrage Neuware - Master's Thesis from the year 2019 in the subject Mathematics - Statistics, grade: 1,0, University of Bamberg (Statistik und Ökonometrie), language: English, abstract: In this thesis, the similarity, the complexity, as well as the evolution of English song lyrics over the past five decades will be examined with the help of statistical methods. Hence, the central research question of this thesis is: Can information gained by Natural Language Processing and statistical topic modelling be used to determine whether and to what extent song lyrics of various genres changed over the course of the past 50 years Based on this, the goals of this thesis are:determining how similar songs of five diverse genres (alternative, country, pop, rock, and hip-hop) are, as measured by text statistics and text features that are composed by Natural Language Processing (NLP) and text mining methods. Additionally, using these methods as well as an attempt to find out whether song lyrics are becoming less complex and therefore less sophisticated And, finally, the main target of this thesis set for itself, computing statistical topic models by applying Latent Dirichlet Allocation (LDA), to analyse how similar the topics of songs are and whether they changed over time. This will be conducted by calculating similarity measures on the per-topic-per-word probability distributions that are output of the LDA models. 112 pp. Englisch, Books.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
Druck auf Anfrage Neuware - Master's Thesis from the year 2019 in the subject Mathematics - Statistics, grade: 1,0, University of Bamberg (Statistik und Ökonometrie), language: English, abstract: In this thesis, the similarity, the complexity, as well as the evolution of English song lyrics over the past five decades will be examined with the help of statistical methods. Hence, the central research question of this thesis is: Can information gained by Natural Language Processing and statistical topic modelling be used to determine whether and to what extent song lyrics of various genres changed over the course of the past 50 years Based on this, the goals of this thesis are:determining how similar songs of five diverse genres (alternative, country, pop, rock, and hip-hop) are, as measured by text statistics and text features that are composed by Natural Language Processing (NLP) and text mining methods. Additionally, using these methods as well as an attempt to find out whether song lyrics are becoming less complex and therefore less sophisticated And, finally, the main target of this thesis set for itself, computing statistical topic models by applying Latent Dirichlet Allocation (LDA), to analyse how similar the topics of songs are and whether they changed over time. This will be conducted by calculating similarity measures on the per-topic-per-word probability distributions that are output of the LDA models. 112 pp. Englisch, Books.
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How Did English Songs Evolve? Retrieving Information from Song Lyrics Via Natural Language Processing and Statistical Topic Modeling (eBook, PDF) (2019)
~EN NWISBN: 9783346376244 bzw. 3346376249, vermutlich in Englisch, GRIN Verlag, neu.
Lieferung aus: Deutschland, Sofort per Download lieferbar, Versandkostenfrei innerhalb von Deutschland.
Master's Thesis from the year 2019 in the subject Mathematics - Statistics, grade: 1,0, University of Bamberg (Statistik und Ökonometrie), language: English, abstract: In this thesis, the similarity, the complexity, as well as the evolution of English song lyrics over the past five decades will be examined with the help of statistical methods. Hence, the central research question of this thesis is: Can information gained by Natural Language Processing and statistical topic modelling be used to determine whether and to what extent song lyrics of various genres changed over the course of the past 50 years? Based on this, the goals of this thesis are:determining how similar songs of five diverse genres (alternative, country, pop, rock, and hip-hop) are, as measured by text statistics and text features that are composed by Natural Language Processing (NLP) and text mining methods. Additionally, using these methods as well as an attempt to find out whether song lyrics are becoming less complex and therefore less sophisticated And, finally, the main target of this thesis set for itself, computing statistical topic models by applying Latent Dirichlet Allocation (LDA), to analyse how similar the topics of songs are and whether they changed over time. This will be conducted by calculating similarity measures on the per-topic-per-word probability distributions that are output of the LDA models.
Master's Thesis from the year 2019 in the subject Mathematics - Statistics, grade: 1,0, University of Bamberg (Statistik und Ökonometrie), language: English, abstract: In this thesis, the similarity, the complexity, as well as the evolution of English song lyrics over the past five decades will be examined with the help of statistical methods. Hence, the central research question of this thesis is: Can information gained by Natural Language Processing and statistical topic modelling be used to determine whether and to what extent song lyrics of various genres changed over the course of the past 50 years? Based on this, the goals of this thesis are:determining how similar songs of five diverse genres (alternative, country, pop, rock, and hip-hop) are, as measured by text statistics and text features that are composed by Natural Language Processing (NLP) and text mining methods. Additionally, using these methods as well as an attempt to find out whether song lyrics are becoming less complex and therefore less sophisticated And, finally, the main target of this thesis set for itself, computing statistical topic models by applying Latent Dirichlet Allocation (LDA), to analyse how similar the topics of songs are and whether they changed over time. This will be conducted by calculating similarity measures on the per-topic-per-word probability distributions that are output of the LDA models.
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How Did English Songs Evolve? Retrieving Information from Song Lyrics Via Natural Language Processing and Statistical Topic Modeling (2017)
~EN PB NW RPISBN: 9783346376251 bzw. 3346376257, vermutlich in Englisch, GRIN Verlag, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, Ria Christie Collections [59718070], Uxbridge, United Kingdom.
PRINT ON DEMAND Book; New; Publication Year 2017; Fast Shipping from the UK. Books.
PRINT ON DEMAND Book; New; Publication Year 2017; Fast Shipping from the UK. Books.
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How Did English Songs Evolve? Retrieving Information from Song Lyrics Via Natural Language Processing and Statistical Topic Modeling
~EN PB NWISBN: 3346376257 bzw. 9783346376251, vermutlich in Englisch, GRIN Verlag, Taschenbuch, neu.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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How Did English Songs Evolve? Retrieving Information from Song Lyrics Via Natural Language Processing and Statistical Topic Modeling
~EN NW EB DLISBN: 9783346376244 bzw. 3346376249, vermutlich in Englisch, Droemer, München, Deutschland, neu, E-Book, elektronischer Download.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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How Did English Songs Evolve? Retrieving Information from Song Lyrics Via Natural Language Processing and Statistical Topic Modeling (2019)
~EN PB NW RPISBN: 9783346376251 bzw. 3346376257, vermutlich in Englisch, 112 Seiten, Droemer, München, Deutschland, Taschenbuch, neu, Nachdruck.
Lieferung aus: Deutschland, Versandkosten nach: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, Moluna GmbH, [5901482].
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Von Händler/Antiquariat, Moluna GmbH, [5901482].
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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