A Multi-Categorization Method of Text Documents using Fuzzy Correlation Analysis

Transcription

1 Poceedg of the 0th WE Iteatoal Cofeece o PPLIED MTHEMTIC, Dalla, Texa, U, Novembe -3, Mult-Categozato Method of Text Documet ug Fuzzy Coelato aly NNCY P. LIN, HO-EN CHUEH Deatmet of Comute cece ad Ifomato Egeeg, Tamag Uvety, 5 Yg-chua Road, Tamu, Tae, TIWN, R.O.C. acyl@mal.tu.edu.tw @90.tu.edu.tw btact: - I th ae, we ooe a ovel method baed o fuzzy coelato aaly to mult-categozato of text documet. fuzzy coelato aaly whch ca how the tegth of lea elatoh betwee two fuzzy attbute, ad the decto of the elatoh, ued to meaue the tegth of elatoh betwee text documet ad the edefed categoe. ccodg to the oete of fuzzy coelato coeffcet, ad by ug gfcace tet, we ca tell the categoe wth gfcatly otve elatoh to a text documet, ad deteme whch categoe to be aged to a text documet. Key-Wod: - Mult-Categozato, gle-categozato, Fuzzy Coelato aly, Lea Relatoh, Fuzzy ttbute, gfcace Tet Itoducto Kowledge dcovey ad data mg [6, 8] em-tuctued o utuctued data have become moe ad moe motat thee day. Oe of the ctcal ue categozato of text documet. Oday categozato ocedue the to ag each text documet to oe ad oly oe edefed categoy baed o t cotet, whch ca be called a gle-categozato. ut, thee ae fact that eed to be otced, cotet of a text documet may be volved dffeet ue, o the edefed categoe may be elated; theefoe, gle-categozato may ot alway be a good way, ad to allow a text documet to be aged to moe tha oe aoate categoy eem eaoable. Recetly, may method have bee ooed to deal wth gle-categozato of text documet [6, 8,,, 3], but they ae ot utable way to deal wth mult-categozato of text documet. To mult-categozato of text documet, a ovel dea, fuzzy coelato ued text mult-categozato oblem, ooed [4]. fuzzy coelato aaly ca how the tegth of lea elatoh betwee two fuzzy attbute, ad the decto of the elatoh [3]. I th ae, we adot the fuzzy coelato aaly to meaue the tegth of elatoh betwee the text documet ad the edefed categoe. The, accodg to the ug gfcace tet [, 5], we ca tell the categoe wth gfcatly otve elatoh to a text documet, ad thu deteme whch categoe to be aged to a text documet. Th ae ogazed a follow: I ecto, we exla the cocet of mult-categozato of text documet ad the eao why mot of the gle-categozato method ae ot utable fo mult-categozato. I ecto 3, the eetal cocet of ou ooed method, fuzzy coelato aaly, wll be exlaed. I ecto 4, we teet how to ue fuzzy coelato coeffcet ad the gfcace tet olvg the multcategozato of text documet. I ecto 5, a mle exemet ad eult ae dlayed. ecto 6 ou cocluo. Pelmay The two ctcal ue categozato ocedue of text documet ae how to meaue the tegth of elatoh betwee the text documet ad the edefed categoe, ad how to deteme whch categoy hould be aged to each documet. Fo the ft ue, the two commo ued model ae vecto ace model ad obablty model [4, 6, 8,,, 3]. I vecto ace model, the dtace o agle betwee two dffeet data ot o vecto ued to eeet the tegth of elatoh betwee a text documet ad a edefed categoy. I obablty model, the obablty of a text documet belog to a edefed categoy ued to eeet the tegth of elatoh betwee th text documet ad th

2 Poceedg of the 0th WE Iteatoal Cofeece o PPLIED MTHEMTIC, Dalla, Texa, U, Novembe -3, edefed categoy. fte we have obtaed the tegth of elatoh betwee all text documet ad all edefed categoe, the ext te to deteme the categoy of each text documet. Fo gle-categozato of text documet, to deteme the categoy of each text documet, all we eed to do to ag each text documet to the categoy wth the hghet tegth of elatoh. O the othe had, fo mult-categozato of text documet, a tutve way to deteme the categoy of each documet to et a thehold. The a text documet ca be aged to eveal edefed categoe, f the tegth of elatoh betwee th text ad thoe categoe, eectvely, ae hghe tha the thehold. I may actcal cae, howeve, to decde a aoate thehold fo mult-categozato ocedue a vey dffcult ta. Fo examle, a vecto ace model, the dtace betwee a text documet T ad thee edefed categoe, ad C ae a the followg table. Table: dtace betwee text documet T ad categoe, adc. categoy text documet T We ca ee that d,c C d, 0.90 < d, < d, 0.8 d,. d, C 0.7 Fo gle-categozato, T hould be aged to categoy C, becaue the dtace betwee T ad categoy C the hotet. Ca we alo ag T to categoy o to categoy fo multcategozato? Clealy, thee o fomato fo u to at mag the deco. The eao that, whe dtace o agle ad obablte ae ued to eeet the tegth of elatoh betwee a text documet ad the edefed categoe, the fomato we ca oly obta the ode of the tegth of elatoh betwee a text documet ad all edefed categoe, but we ca t tell the categoe wth gfcatly otve elatoh to th text documet. To ovecome th oblem ad multcategozato of text documet, a ovel method baed o fuzzy coelato aaly [3] ooed hee. y fuzzy coelato aaly, we ca ot oly ow the tegth of elatoh betwee a text documet ad all the edefed categoe, but alo ca obta moe fomato, whch the fact whethe the text documet ad the edefed categoe ae otvely o egatvely elated. aed uo thee fomato thu obtaed, we ca eue that o text documet aged to the categoe zeo o egatvely elated to t. lo, accodg to the ug gfcace tet [, 5], we ca tell the categoe wth gfcatly otve elatoh to a text documet, ad ag multle aoate categoe fo each text documet. What the fuzzy coelato coeffcet ad how t ued to meaue the tegth of elatoh betwee a text documet ad a edefed categoy wll be exlaed the ext ecto. 3 Fuzzy Coelato Coeffcet The coelato coeffcet betwee two fuzzy et called fuzzy coelato coeffcet. It geat ueful, f we wat to ow the elatoh betwee two vague vaable o fuzzy attbute. May method have bee ooed to evaluate the coelato coeffcet of fuzzy data [, 3, 7, 9, 4]. Hee, we adot the fomula by L [3], becaue th method ca ovde the moe fomato we eed. uoe thee ae two fuzzy et, F, whee F a fuzzy ace. The fuzzy et ad ae defed o a c uveal et X wth membeh fucto ad. The the fuzzy et ad ca be exeed a: x, x x X, x, x x X, whee : X [ 0, ] ad : X [ 0, ]. ume that thee a adom amle x, x, L, x X, aloe wth a euece of aed data, x, x, x, x, x, x,, x, x, x, whch coeod to the gade of the membeh fucto of fuzzy et ad defed o X. d the the coelato coeffcet betwee the fuzzy et ad,, whee,, :, 3

3 Poceedg of the 0th WE Iteatoal Cofeece o PPLIED MTHEMTIC, Dalla, Texa, U, Novembe -3, , x x x 5, x 6, x x 9, 0. 7, 8, 4, the covaace of fuzzy et ad. ad ae the aveage membeh gade of fuzzy et ad ove the adom amle,,,, ae the vaace of fuzzy attbute ad, eectvely. ome oete of the fuzzy coelato coeffcet ae tated hee. I te of the fact that value of the fuzzy membeh fucto ae cotaed betwee [0,], the value of the coelato coeffcet deved fom 3 le betwee [-,], whch wll how u ot oly the degee of elatoh betwee the fuzzy et, but alo the fact whethe thee two et ae otvely o egatvely, elated. If cloe to, the the fuzzy et ad ae hghly elated. If, cloe to 0, the the fuzzy et ad ae baely elated. If 0, the the fuzzy et ad ae, > otvely elated. If 0, the the fuzzy, < et ad ae egatvely elated. If 0,, the the fuzzy et ad have o elatoh at all. Next, how fuzzy coelato coeffcet ued to meaue the tegth of elatoh betwee a text documet ad a edefed categoy wll be exlaed a follow. 4 Mult-Categozato Method aed o Fuzzy Coelato aly I ou ooed method, the fuzzy coelato aaly ued to meaue the tegth of lea elatoh betwee the text documet ad the edefed categoe. The, accodg to the ug gfcace tet, we ca tell the categoe wth gfcatly otve elatoh to a text documet, ad thu ag multle aoate categoe fo each text documet. 4. Fuzzy coelato coeffcet betwee text documet ad edefed categoe ume that thee ae m edefed categoe, ad we adomly elect ome text documet fom each of the edefed categoe. ll of the wod fom thee documet ae ooled lted ad umbe of documet each wod aea ae ecoded accodgly, to fom a feuecy lt, FL. FL w, N w L }, { FL whee N w the feuecy of wod w aea the collecto, FL the total umbe of wod FL. mlaly, fom each categoyc, Lm, we alo adomly elect ome text documet to fom a categoy feuecy ltcfl. CFL w, N w j L }, { j j whee N w j the feuecy of wod w j aea the documet of categoy C, the total umbe of wod CFL. ce thee wll be a eomou umbe of wod FL ad CFL, theefoe, we chooe a total of wod fom FL U CFL U CFL ULU CFL m c, a ou eywod amle et, KW. KW { w, w, L, w } 3. The followg te to meaue the tegth of elatoh betwee each text documet ad all the edefed categoe. Let w ad w be the degee of motace of eywod w a text documet T ad be the degee of motace of eywod w a edefed categoyc. The, the fuzzy coelato coeffcet,,, ued to eeet the tegth of elatoh

4 Poceedg of the 0th WE Iteatoal Cofeece o PPLIED MTHEMTIC, Dalla, Texa, U, Novembe -3, betwee the text documet D ad the edefed categoyc., whee,,, 4 w w w 6, w 7, w w 0, 8, 9, 5,. fte the tegth of elatoh betwee each text documet ad each edefed categoy ae obtaed by fuzzy coelato aaly, the gfcace tet ued to deteme the categoe that a text documet hould be aged to. 4. gfcace tet of fuzzy coelato coeffcet ccodg to ecto 3, the fuzzy coelato coeffcet,,, betwee [-,]. lo, f, cloe to, the the text documet D ad the edefed categoyc ae hghly elated. If, cloe to 0, the the text documet D ad the edefed categoy C ae baely elated. If, > 0, the D ad C ae otvely elated. If, < 0, the D ad C ae egatvely elated. If, 0, the D ad C have o elatoh at all. Thoe fomato wll be geatly ueful fo u to categozato of text documet, becaue we ca eue that o text documet aged to the categoe zeo o egatvely elated to t. lo, by ug gfcace tet of the fuzzy coelato coeffcet betwee a text documet ad all edefed categoe, ad we ca tell the categoe wth gfcatly otve elatoh to th documet. The gfcace tet tated a follow [, 5]. ume that umbe of the eywod, ad the fuzzy coelato coeffcet betwee the text documet D ad the edefed categoy C,. We wat to tet that thee a gfcatly otve elatoh betwee the text documet D ad the edefed categoy C. Thu, ou ull hyothe H 0 : ρ.00, ad the alteatve hyothe H : ρ > Hee, we emloy the t tet [, 5], t, 4., Comae the value of the t tet to t α. α the level of gfcace ad the degee of feedom. If we obta a value geate tha, the we eject the ull hyothe t α ρ. 00, ad mae the cocluo that thee a gfcatly otve elatoh betwee the text documet D ad the edefed categoy C. Th oce eeated fo all the text documet to fd the categoe wth gfcatly otve elatoh, ad thu we ca ag the aoate categoe fo each text documet. 5 Exemet ad Reult mle exemet caed out by ug the data fom Electoc Thee ad Detato ytem of the Natoal Cetal Lbay [0]. We elect 3 toc mg aocato ule, cluteg, ad clafcato a ou edefed categoe. Thee toc ae elated ad the bac techue of data mg. To mlfy, we elect ome thee about thee thee toc, have all the ue-defed eywod lted ad ecod the feuece they aea to fom FL, ad the categoy feuecy lt of thee thee edefed categoe.

5 Poceedg of the 0th WE Iteatoal Cofeece o PPLIED MTHEMTIC, Dalla, Texa, U, Novembe -3, Fom FL ad the categoy feuecy lt, we adomly chooe 4 wod a ou KW, ad w KW, the membeh fucto w ad w, ae ued to eet the gade of motace a the, ay D, ad a edefed categoy, ayc. N P w, NWP w N w w 3, ND whee N w the feuecy of w aea the D ; NW umbe of eywod the D ; N w the feuecy of w aea the documet of categoy C ; ND umbe of documet categoy C. Next, we ue ome othe thee to tet ou ooed method decbed ecto 4. oth of the Recall Rate, R, ad the Peco Rate, P, [4] ae ued a the tet ctea. The eult of ou exemet ae dlayed Table. Table: the eult of ou exemet ad the level of gfcace α Recall Rate R Pec o Rate P mg aocato ule cluteg clafcato The eult of ou exemet how the efomace of ou ooed method well. 6 Cocluo I may categozato ocedue, the oto that a text documet jut ca be aged to oe ad oly oe categoy may be doubted. Theefoe, evou ae, we ooe a ew thought that a ulabeled text documet could be aged to moe tha oe categoy eaoably. Howeve, u to ow, may method ae ooed to glecategozato of text documet, whch few fo mult-categozato. Thu, ou uoe hee to toduce a ew method, fuzzy coelato baed method, to deal wth mult-categozato of text documet. fuzzy coelato aaly whch ca how the tegth of the lea elatoh betwee two fuzzy attbute, ad the decto of the elatoh, ued hee to meaue the tegth of the lea elatoh betwee text documet ad the edefed categoe. ccodg to the ug gfcace tet, we ca tell the categoe wth the gfcatly otve elatoh to a text documet, ad deteme whch categoe to be aged to a text documet. Refeece: []. F. old, Mathematcal tattc, Petce- Hall, New Jeey, 990. [] H. utce, P. ullo, Coelato of tevalvalued tutotc fuzzy et, Fuzzy et ad ytem, Vol. 74, 995, [3] D.. Chag, N. P. L, Coelato of Fuzzy et, Fuzzy et ad ytem, Vol. 0, 999,. -6. [4] Hao-E Chueh, Nacy P. L, Fuzzy Coelato ued Text Mult-Categozato Poblem, Poceedg of the tfcal Neual Netwo I Egeeg, 00, [5]. Dowdy,. Weade, tattc fo Reeach, Joh Wley & o, 983. [6] M. H. Duham, Data mg, Itoductoy ad dvaced Toc, Peao Educato, Ic., 003. [7] T. Geteo, J. Mao, Coelato of tutotc fuzzy et, Fuzzy et ad ytem, Vol. 44, 99, [8] J. Ha, M. Kambe, Data mg: Cocet ad Techue, cademc Pe, 00. [9] D. H. Hog,. Y. Hwag, Coelato of tutotc fuzzy et obablty ace, Fuzzy et ad ytem, Vol.75, 995,.77-8 [0] htt://etd.cl.edu.tw/theab/eglh_te/each _mle_eg.j [] Taeho C. Jo, Text categozato wth the cocet of fuzzy et of fomatve eywod, IEEE Iteatoal Fuzzy ytem Cofeece Poceedg, Vol., 999, [] ehalfa, M., ead,., Mouad,., Text categozato ug the em-ueved fuzzy c-mea algothm, NFIP Iteatoal Fuzzy Ifomato Poceg ocety, 999,

6 Poceedg of the 0th WE Iteatoal Cofeece o PPLIED MTHEMTIC, Dalla, Texa, U, Novembe -3, [3] Ymg Yag, X Lu, e-examato of text categozato method, Poceedg of the d ual Iteatoal CM IGIR cofeece, 999,.4-49 [4] C. Yu, Coelato of fuzzy umbe, Fuzzy et ad ytem, Vol. 55, 993,