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NLP
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== Data mining==
http://en.wikipedia.org/wiki/Principal_components_analysis
== NLP Language Research==
=== generation of conjectures ===
* 'Automatic Conjecture Generation in the Digital Humanities' by Patrick Juola and Ashley Bernola
** http://twitter.com/conjecturator
=== resources ===
* Wordnet
* Framenet
* OpenConceptNet http://conceptnet.media.mit.edu/
* Cyc
* http://www.cse.ohio-state.edu/~dbyron/788AU06/initial-handout.pdf
=== basic Content Analysis ===
* http://www.williamlowe.net/software/ca-in-python.html
=== Identity as a Variable ===
* http://www.ucd.ie/euiteniba/pdf/Identity%20as%20a%20Variable.pdf
=== Closed Captioning ===
* http://www.dcmp.org/captioningkey/
* http://en.wikipedia.org/wiki/Closed_captioning
* Caption it yourself http://www.dcmp.org/ciy/
=== Teleprompter ===
Language for performance
[[Teleprompter]]
=== Wordnet similarity ===
wordnet::similarity word vectors
* coffee#n#1: nutmeg, preparation, coffee_tree, caffeine, pulverized, coffee, arabia, tea, shelf_life, packed, hot_water, drinking, topped, java, lemon_peel, ordered, cognac, irish_whiskey, beverage, perforated, cup, sweetened, infusion, espresso, cream, boiling, dehydrated, finely, whipped_cream, stimulating, bitter, cinnamon, alkaloid
* cup#n#1: loaded, drunk, disposable, mustache, coffee, boxlike, tea, saucer, footed, drinking, eucharistic, collectively, tableware, bowl, cup, standardized, greece, rim, toast, missing, ancient_greek, drinking_vessel
* rifle#n#1: automatic_rifle, loads, loading, rifle, action_mechanism, bore, barrel, butt_end, breech, cartridge, fired, sliding, firearm, shotgun, lever, armored, shoulder_holster, portable, lifted, semiautomatic, forward_motion, rifled
* work#n#1: dry_rot, busywork, willing, machine_tool, technology, practical, barn, shiny, undertaking, productive, wages, inquiring, waiting, unit_of_time, preliminary, cleansing, substitute, incomplete, obliged, operations, a_great_deal, rubbing, washed, separately, ophelia, outstanding, interesting, waxing, stocks, attending, papers, labor, thoroughly, heavy_lifting, wasnt, municipal, succeed, missionary, hoped, further, mechanical, medical_care, barber, assigned, meager, budget, course_of_study, attempted, disadvantaged, boss, routine, damaging, close_to, done_for, grade, directed, systematically, recreational, duties, checked, shining, shoes, piece_of_work, polishing, sunday, soap, gawkers, leave_of_absence, improve, no_longer, cleaning, housewife, handling
* neck: sternum, collarbone, hanging, immunity, human_being, cartilaginous, externally, cervix, aids, elderly, body_part, glandular, rings, flex, mastoid, clavicle, admired, occipital_bone, arteries, larynx, membranous, inhaled, aorta, fold, obliquely, artery, ductless, spine, on_fire, chin, graceful
* rifle#n#1 <-> neck#n#1 = 0.0728235790450328
=== Generative Video through NLP ===
* making edits based on semantic content
** sequence
** cut points?
** decisions based on character names?
* aesthetic strategies for text
** side-scrolling text
** intertitles
** subtitles
** titles
* aesthetic strategies for photos
** Ken Burns effect
** simulated motion
*** motion blur [[Main_Page#Motion Estimation]]
*** camera shake
*** applying motion parameters extracted from real-life situation
* aesthetic strategies for video
** specifically... diverse collections of heterogenous clips and documentation
** video collection strategies
=== similarity measures ===
Calculating the similarity of two phrases, with the goal of finding more related matches. Example: "ocean at night" to "still life, objects around the studio" versus "cat tails at the ocean"
* http://www.google.com/search?q=calculate+similarity+of+two+phrases&hl=en&start=20&sa=N
* http://stackoverflow.com/questions/70560/how-do-i-compare-phrases-for-similarity
* http://en.wikipedia.org/wiki/Document_classification
* Phrase-based Document Similarity Based on an Index Graph Model http://www2007.org/papers/paper632.pdf
* http://pami.uwaterloo.ca/pub/hammouda/hammouda_icdm02.pdf
[[NLP]]
Optical Character Recognition
* tesseract-ocr [http://code.google.com/p/tesseract-ocr/]
* ocropus [http://code.google.com/p/ocropus/] layout analysis, tesseract is a plugin
[http://www.hpcwire.com/offthewire/University-of-Reading-Scientists-Study-Word-Evolution-40356217.html word evolution study at University of Reading]
* Professor Mark Pagel [http://www.evolution.reading.ac.uk/ http://www.evolution.reading.ac.uk/]
* ThamesBlue
[[language associations]]
Closed Captioning
* http://en.wikipedia.org/wiki/Closed_captioning
=== Electronic Literature as Performance ===
* http://www.drunkenboat.com/db10/05ele/elite.html