, Hindi: 163221 Hindi word forms from 68788 lemmas

, Marathi: 72312 Marathi word forms from 6026 lemmas

, IV.2.2.1.3 Bilingual lexical resources We obtained the as a bilingual resource

, HI-UNL dictionary from CFILT-IITB with 136710 Universal words and 65156 lemmas

, Hindi-English Shabdkosh dictionary with 22756 entries

, Hindi-English Apertium dictionary with 30463 entries

, Available resources for tweets in Japanese IV.2.2.2.1 Tweet resources For Japanese tweets, we use a collection of 3, IV.2.2.22M tweets collected by Prof. Kitamoto (NII, Tokyo) during the whole of, 2014.

, We used samples from this collection to make evaluation experiments on Japanese tweets within SUFT-1

, IV.2.2.2.2 Lexical resources for Japanese-French and Japanese-English Resources available on the JIBIKI/PAPILLON platform 80 have been used for SUFT-1

, Japanese-French: The CESSELIN dictionary, with 82K entries

. Japanese-english, The JMDICT dictionary, with 48K entries

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S. Yang and A. L. Kavanaugh, Half-Day Tutorial : Collecting, Analyzing and Visualizing Tweets using Open Source Tools, Proceedings of the 12th Annual International Conference on Digital Government Research, pp.374-375, 2011.

X. Yang, Y. Guo, Y. Liu, and H. Steck, A survey of collaborative filtering based social recommender systems, Computer Communications, vol.41, pp.1-10126, 2014.
DOI : 10.1016/j.comcom.2013.06.009

Z. Ying, Modèles et outils pour des bases lexicales " métier " multilingues et contributives de grande taille, utilisables tant en traduction automatique et automatisée que pour des services dictionnairiques variés. (Doctoral dissertation, Alpes), 2016.

A. Zielinski, U. Bügel, . Hindi, . Marathi, and E. Gujarati, Multilingual Analysis of Twitter News in Support of Mass Emergency Events DVM file contents ** DVM: morphological "variables" (attributes) for an AM phase aiming at handling indian tweets, Proceedings of International Conference on Information Systems for Crisis Response and Management (ISCRAM), pp.5-10, 2012.

, ** For the moment, the language code is HIN (Hindi), but we may change it later to ITW (Indian TWeets)

-. Exclusive,

*. Language, . En-english, . Fr-french, . Hi-hindi, . Mr-marathi et al.,

L. ==, . En, . Fr, . Hi, . Mr et al.,

*. Tactical-variable, the FINAL value indicates that we want to force a unique result for AM, TAKTIK == ( FINAL )

-. , Non-exclusive variables (set values)

, ** Dictionaries of bases (radicals) and affixes

D. ==, , 2006.

*. By, 1: prefixes (all languages considered, but they will contain their language id) 2: radicals (Hindi) 3: suffixes (all languages considered, but they will contain their language id) 4: radicals (English) 5: radicals (Marathi, p.radicals

*. Typography, capitalization) of an occurence (indian tweets often contain English words!)

T. ==-(-allupp, *. All-uppercase, *. Firstup, and . Uppercase, ABBREV, ** ABBREViation ending with a period. SHILEFT ** SHort I goes

2. Dvs-file-contents and *. Dvs, syntactic" (actually syntactic, morphological or semantic!) variables" (attributes) for an AM phase aiming at handling Indian tweets, potentially multilingual --containing Hindi

, ** Creation: 13/09, 2016.

*. Updated and . Ritesh, 16: added categories for Number and Person ** Updated by Ritesh

*. Subcategory, . Nouns, *. Subn-==-(-c, *. P. Common, and . V. Proper,

S. Spatio,

*. Subcategory, . Verbs, *. Subv-==-(-m, and . Main,

A. Auxiliary,

, Appendix 3 116, p.126

*. Subcategory and . Pronouns,

S. ==, *. Pr, . Personal, *. Rf, . Reflexive et al.,

, ** Subcategory of adJuncts of nouns

S. ==-(-adj, *. Q. Adjective, and . Quantifier,

*. Subcategory-of-demonstrative and *. *. Subd-==-(-ab, ABsolute --that. RL, ** ReLative --Dravidian language ??? --seems to be wrong. WH ** WH-demonstrative --Dravidian language ??? --seems to be wrong. )

*. Subcategory,

S. ==, *. Mn, . Manner, *. Lc, . Location et al.,

D. Degree,

S. ==-(-rl, *. , V. , *. N. , and *. *. , , pp.Nominal -building

C. ,

, ** Subcategory of postpositions: none

*. Subcategory,

*. Subcategory and . Punctuations,

S. == and *. *. Sipul, SIngle PUnctuation Left: "itemizer" such as hyphen or dash after a line break like \n or <br> or </h1>, or "enumerator" such as 1-2-4-a) or ii)

S. and *. *. , SIngle PUnctuation Right (period, comma, ellipsis); colon, semi-colon, interrogation sign, exclamation sign)

S. and *. *. , SIngle HTml tags --monotags (ex: <img a-v list />, to be preprocessed into for example %%HTMMONOTAG_img_24

D. and *. *. , DOuble PUnctuation Left (opening quote, parenthesis, bracket, brace, parenthetical dash)

D. and *. *. , DOuble PUnctuation Right (closing quote, parenthesis, bracket, brace, parenthetical dash)

D. and *. *. , DOuble HTml tags Left (<i a-v list>, to be preprocessed into for example %%HTMOPENTAG_i_25

D. and *. *. , DOuble HTml tags Right (</i>, to be preprocessed into for example %%HTMCLOSETAG_i_25

X. ,

*. Subcategory, . Subem, *. Emolist, . Emoji-list, *. Phatic et al.,

, ** Subcategory of tweet-specific occurences, p.126

S. ==, *. Twcd, and . Command,

T. Address,

, Subcategory of Out of Text elements (hors-texte in French

S. ==, ** image or icon, can function as a proper singular noun (for example, %%IMG_15), IMAGE

M. and *. *. , can function as a noun (for example, $ab+2$ preprocessed as %%MEXP_13)

M. and *. *. , can function as noun or verbal kernel (for example, $xy>2$ preprocessed as %%MREL_43)

P. , *. *. , and B. , , p.123

P. , *. *. , and O. Capitan, , pp.10-11

, ** chemical element like H_2O or Al_2O_3, possibly preprocessed as %%CHEMELEM_22, CHEMELEM

C. and *. *. , CHEMical FORMula (like benzines, preprocessed as %%CHEMFORM_23. SYSSTR, ** like menu names, menu items, command lines, system answers

S. , *. Symbol, £. , and %. ,

N. and *. Nominal--building,

U. Unknown,

*. Morphosyntactic,

C. ==-(-n, *. V. Noun, *. P. Verb, and *. Pronoun,

J. and *. Nominal-modifier,

D. , *. A. Demonstrative, and *. L. Adverb,

P. and *. C. Postposition,

P. and *. Punctuation,

E. , *. Emoji, and . Phatic,

O. and *. *. , Out of Text (hors-texte in French

T. and *. Command,

R. Residual,

C. Ma-input and :. ???, ??, Total Output : 2 [ Root : ?"??, Class : , Category : verb, Suffix : Null ] [ Gender : x, Number : x, Person : x, Case : x, Tense : x, Aspect : x

, Category : verb, Suffix : ?? ] [ Gender : +masc, Number : -pl, Person : x, Case : x, Tense : x, Aspect : +perfect, Mood, Set of Roots and Features

:. Token, T. ?&, and . Output, Set of Roots and Features

, Token : ?? #??&, issue.1

, Number : +pl, Person : x, Case : +oblique, Tense : x, Aspect : x, Mood : x ] [ Gender : -masc, Number : +pl, Person : x, Case : +oblique, Tense : x, Aspect : x, Mood : x ] [ Gender : -masc, Number : +pl, Person : x, Case : +oblique, Tense : x, Aspect : x, Mood, Set of Roots and Features

!. Token, T. ???-??-', and . Output, Set of Roots and Features

, Token : ?? ???, issue.1

, Category : verb, Suffix : ? ] [ Gender : +masc, Number : +pl, Person : x, Case : x, Tense : x, Aspect : +perfect, Mood, Morphological analyses output from IIIT public web service 86

:. Input and . ???, Address TOKEN Features (af='root,cat,gen,num,per,case,tam

, ??,adj,m,sg,d,'> <fs af='?"??,n,m,sg,3,d,0,0'> <fs af=

!. ??, $. ??-'<fs-af=-'!, . ??, and . ??, 0'> 5 ?? ??? <fs af='?? ?,v,any,sg,2,?,e' hon='y'> <fs af='?? ?,v,any,pl, p.122126

, Appendix 7 Morphological analyses of code-mixed tweets by ATEF 1

?. ??, ?. ????, and . ???-???-?-??-???-?????-'????-????-'<-/-tweet>, UL('ULTXT') 2 '': UL('ULFRA') 3 '': UL('ULOCC')

, PER(TD) 5 '': UL('ULOCC')

, NUM(SNG,PLR) 7 '': UL('ULOCC')

?. ????-': and . Ul, CAT(RD) 9 '': UL

, CAT(RD) 11 '': UL

?. ???, CAT(RD) 13 '': UL

, (PP) 15

, CAT(RD) 17 '': UL('ULOCC') 18 '?????': UL('?????'), CAT(RD) 19 '': UL('ULOCC') 20 ''????': UL, CAT(RD) 21 '': UL('ULOCC') 22 '????'': UL('????_'), CAT(RD) 23 '': UL('ULOCC') 24 '<tweet LANG (XML), p.UL

R. and ?. ?????, UL('ULFRA') 4338 '': UL('ULOCC') 4339 'RT': UL('RT'), CAT(RD) 4340 '': UL('ULOCC')

, 4341 '@viveklkw:': UL('@viveklkw:'), CAT(RD) 4342

, 4344 UL('ULOCC') 4345 ' ! ': UL, CAT(RD) 4346 '': UL

, 4347, CAT(RD) 4348 '': UL

, NUM(SNG) 4350 '': UL

?. , CAT(RD) 4352 CAT(RD) 4356 '': UL('ULOCC') 4357 '????': UL CAT(RD) 4358 '': UL('ULOCC') 4359 '?? ': UL, CAT(RD) 4354 '': UL('ULOCC') 4355 '???': UL('???') CAT(RD) 4360 '': UL('ULOCC') 4361 '??? ??': UL('??? ??'), CAT(RD) 4362 '': UL('ULOCC') 4363 '????? ': UL('????? '), CAT(RD) 4364 '': UL('ULOCC') 4365 '?? ?? ': UL('?? ?? '), CAT(RD) 4366 '': UL('ULOCC') 4367 '?? ': UL('?? '), CAT(RD) 4368 '': UL('ULOCC') 4369 '..': UL('..'), CAT(RD) 4370 '': UL('ULOCC')

, SUBV(M) 4372 '': UL('ULOCC') 4373 '?? ': UL('?? '), CAT(RD) 4374 '': UL('ULOCC') 4375 '????? ': UL('????? '), CAT(RD) 4376 '': UL('ULOCC')

, Appendix, p.126

, SUBJ(Q) 4378 '': UL('ULOCC')

, SUBV(M) 4380 '': UL('ULOCC') 4381 '??????': UL('??????'), CAT(RD) 4382 '': UL('ULOCC')

, LANG (XML) Appendix 7 125, p.126126