NLP
Web 1T 5-gram Version 1 ldc upenn
ldc new corpora link
Suffix Array Analysis Tutorial of the SALM package
Visual Wordnet [1]
Contents
Word Vectors
Gloss vector overlap http://www.d.umn.edu/~tpederse/Pubs/ijcai03.pdf
Second order co-occurence vectors
Opinion Mining
http://wiki.cse.cuhk.edu.hk/irwin.king/kb/opinionmining
SensiWordNet - a publicly available resource for opinion mining.
Natural Language Interface to a Video Data Model
http://etd.lib.metu.edu.tr/upload/12606251/index.pdf
http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?tp=&arnumber=4061311&isnumber=4061295
Data mining
NLP Language Research
generation of conjectures
- 'Automatic Conjecture Generation in the Digital Humanities' by Patrick Juola and Ashley Bernola
resources
- Wordnet
- Framenet
- OpenConceptNet http://conceptnet.media.mit.edu/
- Cyc
- http://www.cse.ohio-state.edu/~dbyron/788AU06/initial-handout.pdf
basic Content Analysis
Identity as a Variable
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
word evolution study at University of Reading
- Professor Mark Pagel http://www.evolution.reading.ac.uk/
- ThamesBlue
Closed Captioning