@inproceedings{
    okohonen+katajamaki+honkela_2005,
    editor = {Russell, Ann and Honkela, Timo and Lagus, Krista and P\"{o}ll\"{a}, Matti},
    author = {Kohonen, Oskar and Katajam\"{a}ki, Sakari and Honkela, Timo},
    responsibleperson = "Kohonen,Oskar",
    abstract = "The sonnet is one of the most canonical modes of poetry in Western literature. The English or Shakespearean sonnet falls in to three quatrains in iambic pentameter, with a turn at the end of the line 12 and a concluding couplet often of a summary or epigrammatic character. The turn normally is both semantic and stylistic for the rhyme scheme {\em abab} {\em cdcd} {\em efef} of the first part of the poem changes to a form {\em gg} in the closing couplet. We analyze if the semantic turn, or volta, can be found with statistical analysis of word distributions, using the Self-Organizing Map for exploration and visualization. The Self-Organizing Map is a neural network architecture based on unsupervised learning. We conclude that our methods can be useful for finding semantic and stylistic turns that can then be studied in detail using other methods. We propose extensions to our methods for other literary analysis.",
    month = "June",
    optorganization = "",
    year = "2005",
    optcrossref = "",
    title = "In Search for Volta: Statistical Analysis of Word Patterns in Shakespeare's Sonnets",
    booktitle = "Proceedings of AMKLC'05, International Symposium on Adaptive Models of Knowledge, Language and Cognition",
    note = "Poster",
    optannote = "",
    optvolume = "",
    impactfactor = "A4",
    optseries = "",
    optnote = "",
    optpublisher = "Helsinki University of Technology, Laboratory of Computer and Information Science",
    address = "Espoo, Finland",
    pages = "44--47",
    optnumber = "",
    url = "http://www.cis.hut.fi/AKRR05/papers/amklc05kohonen.pdf",
    flags = "AIRC COG RAE public",
    optkey = "",
    pdf = "InSearchForVoltaFinal.pdf"
}