|
|
|
|
LEADER |
00000nam a2200000Ia 4500 |
001 |
b2655134 |
003 |
CStclU |
005 |
20140726095553.9 |
006 |
m o d |
007 |
cr cnu---unuuu |
008 |
140502s2014 ne o 000 0 eng d |
020 |
|
|
|a 9789027270139 (electronic bk.)
|
020 |
|
|
|a 9027270139 (electronic bk.)
|
020 |
|
|
|a 1306705908 (electronic bk.)
|
020 |
|
|
|a 9781306705905 (electronic bk.)
|
035 |
|
|
|a (NhCcYBP)EBC1682185
|
040 |
|
|
|a NhCcYBP
|c NhCcYBP
|
050 |
|
4 |
|a P98.5 .O25 2014
|
072 |
|
7 |
|a COM
|x 000000
|2 bisacsh
|
082 |
0 |
4 |
|a 006.3
|a 006.35
|2 22
|
100 |
1 |
|
|a Oakes, Michael P.,
|e author.
|
245 |
1 |
0 |
|a Literary detective work on the computer
|h [electronic resource] /
|c Michael P. Oakes.
|
260 |
|
|
|a Amsterdam :
|b John Benjamins Publishing Company,
|c 2014.
|
300 |
|
|
|a 1 online resource.
|
336 |
|
|
|a text
|b txt
|2 rdacontent
|
337 |
|
|
|a computer
|b c
|2 rdamedia
|
338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
533 |
|
|
|a Electronic reproduction.
|b Perth, W.A.
|n Available via World Wide Web.
|
588 |
|
|
|a Description based on print version record.
|
505 |
0 |
0 |
|a Machine generated contents note:
|g 1.
|t Introduction --
|g 2.
|t Feature selection --
|g 2.1.
|t Evaluation of feature sets for authorship attribution --
|g 3.
|t Inter-textual distances --
|g 3.1.
|t Manhattan distance and Euclidean distance --
|g 3.2.
|t Labbe and Labbe's measure --
|g 3.3.
|t Chi-squared distance --
|g 3.4.
|t cosine similarity measure --
|g 3.5.
|t Kullback-Leibler Divergence (KLD) --
|g 3.6.
|t Burrows' Delta --
|g 3.7.
|t Evaluation of feature-based measures for inter-textual distance --
|g 3.8.
|t Inter-textual distance by semantic similarity --
|g 3.9.
|t Stemmatology as a measure of inter-textual distance --
|g 4.
|t Clustering techniques --
|g 4.1.
|t Introduction to factor analysis --
|g 4.2.
|t Matrix algebra --
|g 4.3.
|t Use of matrix algebra for PCA --
|g 4.4.
|t PCA case studies --
|g 4.5.
|t Correspondence analysis --
|g 5.
|t Comparisons of classifiers --
|g 6.
|t Other tasks related to authorship --
|g 6.1.
|t $tylochronometry --
|g 6.2.
|t Affect dictionaries and psychological profiling --
|g 6.3.
|t Evaluation of author profiling --
|g 7.
|t Conclusion --
|g 1.
|t Introduction --
|g 2.
|t Plagiarism detection software --
|g 2.1.
|t Collusion and plagiarism, external and intrinsic --
|g 2.2.
|t Preprocessing of corpora and feature extraction --
|g 2.3.
|t Sequence comparison and exact match --
|g 2.4.
|t Source-suspicious document similarity measures --
|g 2.5.
|t Fingerprinting --
|g 2.6.
|t Language models --
|g 2.7.
|t Natural language processing --
|g 2.8.
|t Intrinsic plagiarism detection --
|g 2.9.
|t Plagiarism of program code --
|g 2.10.
|t Distance between translated and original text --
|g 2.11.
|t Direction of plagiarism --
|g 2.12.
|t search engine-based approach used at PAN-13 --
|g 2.13.
|t Case study 1: Hidden influences from printed sources in the Gaelic tales of Duncan and Neil MacDonald --
|g 2.14.
|t Case study 2: General George Pickett and related writings --
|g 2.15.
|t Evaluation methods --
|g 2.16.
|t Conclusion --
|g 3.
|t Spam filters --
|g 3.1.
|t Content-based techniques --
|g 3.2.
|t Building a labeled corpus for training --
|g 3.3.
|t Exact matching techniques --
|g 3.4.
|t Rule-based methods --
|g 3.5.
|t Machine learning --
|g 3.6.
|t Unsupervised machine learning approaches --
|g 3.7.
|t Other spam-filtering problems --
|g 3.8.
|t Evaluation of spam filters --
|g 3.9.
|t Non-linguistic techniques --
|g 3.10.
|t Conclusion --
|g 4.
|t Recommendations for further reading --
|g 1.
|t Introduction --
|g 2.
|t Shakespeare, Wilkins and "Pericles" --
|g 2.1.
|t Correspondence analysis for "Pericles" and related texts --
|g 3.
|t Shakespeare, Fletcher and "The Two Noble Kinsmen" --
|g 4.
|t "King John" --
|g 5.
|t "The Raigne of King Edward III" --
|g 5.1.
|t Neural networks in stylometry --
|g 5.2.
|t Cusum charts in stylometry --
|g 5.3.
|t Burrows' Zeta and Iota --
|g 6.
|t Hand D in "Sir Thomas More" --
|g 6.1.
|t Elliott, Valenza and the Earl of Oxford --
|g 6.2.
|t Elliott and Valenza: Hand D --
|g 6.3.
|t Bayesian approach to questions of Shakespearian authorship --
|g 6.4.
|t Bayesian analysis of Shakespeare's second person pronouns --
|g 6.5.
|t Vocabulary differences, LDA and the authorship of Hand D 13o --
|g 6.6.
|t Hand D: Conclusions --
|g 7.
|t three parts of "Henry VI" --
|g 8.
|t "Timon of Athens" --
|g 9.
|t "The Puritan" and "A Yorkshire Tragedy" --
|g 10.
|t "Arden of Faversham" --
|g 11.
|t Estimation of the extent of Shakespeare's vocabulary and the authorship of the "Taylor" poem --
|g 12.
|t chronology of Shakespeare --
|g 13.
|t Conclusion --
|g 1.
|t Introduction --
|g 1.1.
|t Overview of the New Testament by correspondence analysis --
|g 1.2.
|t Q --
|g 1.3.
|t Luke and Acts --
|g 1.4.
|t Recent approaches to New Testament stylometry --
|g 1.5.
|t Pauline Epistles --
|g 1.6.
|t Hebrews --
|g 1.7.
|t Signs Gospel --
|g 2.
|t Stylometric analysis of the Book of Mormon --
|g 3.
|t Stylometric studies of the Qu'ran --
|g 4.
|t Condupion --
|g 1.
|t Introduction --
|g 1.1.
|t Differences between cryptography and decipherment --
|g 1.2.
|t Cryptological techniques for automatic language recognition --
|g 1.3.
|t Dictionary approaches to language recognition --
|g 1.4.
|t Sinkov's test --
|g 1.5.
|t Index of coincidence --
|g 1.6.
|t log-likelihood ratio --
|g 1.7.
|t chi-squared test statistic --
|g 1.8.
|t Entropy of language --
|g 1.9.
|t Zipf's Law and Heaps' Law coefficients --
|g 1.10.
|t Modal token length --
|g 1.11.
|t Autocorrelation analysis --
|g 1.12.
|t Vowel identification --
|g 2.
|t Rongorongo --
|g 2.1.
|t History of Rongorongo --
|g 2.2.
|t Characteristics of Rongorongo --
|g 2.3.
|t Obstacles to decipherment --
|g 2.4.
|t Encoding of Rongorongo symbols --
|g 2.5.
|t "Mamari" lunar calendar --
|g 2.6.
|t Basic statistics of the Rongorongo corpus --
|g 2.7.
|t Alignment of the Rongorongo corpus --
|g 2.8.
|t concordance for Rongorongo --
|g 2.9.
|t Collocations and collostructions --
|g 2.10.
|t Classification by genre --
|g 2.11.
|t Vocabulary richness --
|g 2.12.
|t Podzniakov's approach to matching frequency curves --
|g 3.
|t Indus Valley texts --
|g 3.1.
|t Why decipherment of the Indus texts is difficult --
|g 3.2.
|t Are the Indus texts writing? --
|g 3.3.
|t Other evidence for the Indus Script being writing --
|g 3.4.
|t Determining the order of the Markov model --
|g 3.5.
|t Missing symbols --
|g 3.6.
|t Text segmentation and the log-likelihood measure --
|g 3.7.
|t Network analysis of the Indus Signs --
|g 4.
|t Linear A --
|g 5.
|t Phaistos disk --
|g 6.
|t Iron Age Pictish symbols --
|g 7.
|t Mayan glyphs --
|g 8.
|t Conclusion.
|
650 |
|
0 |
|a Computational linguistics
|x Research.
|
650 |
|
0 |
|a Imitation in literature.
|
650 |
|
0 |
|a Plagiarism.
|
650 |
|
0 |
|a Linguistics
|x Research
|x Methodology.
|
650 |
|
0 |
|a Authorship
|x Study and teaching.
|
710 |
2 |
|
|a Ebooks Corporation
|
776 |
0 |
8 |
|i Print version:
|a Oakes, Michael P.
|t Literary Detective Work on the Computer.
|d John Benjamins Publishing Company 2014
|z 1306705908
|
856 |
4 |
0 |
|u https://ebookcentral.proquest.com/lib/santaclara/detail.action?docID=1682185
|z Connect to this title online (unlimited simultaneous users allowed; 325 uses per year)
|t 1
|
907 |
|
|
|a .b26551342
|b 200414
|c 141204
|
998 |
|
|
|a uww
|b
|c m
|d z
|e y
|f eng
|g ne
|h 0
|
919 |
|
|
|a .ulebk
|b 2014-10-15
|
915 |
|
|
|a YBP DDA - Also in ProQuest Academic Complete
|
999 |
f |
f |
|i 85dfc5f0-7a9a-5d68-8eea-48b2d1b465e5
|s 0f33bd4a-04c1-58a9-b166-7c1593ea8a49
|t 1
|