Turkish Keyphrase Extraction Using Multi-Criterion Ranking

Transcription

1 Turkish Kyphrs Extrtion Using Multi-Critrion Rnking Bhır Özmir Dpt. of Computr Enginring Bilknt Univrsity Bilknt Ankr, Turky Emil: Ilys Cikli Dpt. of Computr Enginring Bilknt Univrsity Bilknt Ankr, Turky Emil: Astrt Kyphrss hv n xtnsivly us for inxing n srhing in tss n informtion rtrivl systms. In ition, thy provi usful informtion out smnti ontnt of oumnt. In this ppr, w propos n lgorithm for utomting Turkish kyphrs xtrtion. Svrl fturs of nit phrss r xploit n form th xtrtion tsk s prolm of fining optiml st of nit phrss. W us multi-ritrion rnking to tkl this prolm. I. INTRODUCTION Fining rlvnt oumnt in lirry tss or on Intrnt is hllnging tsk tht rquirs sussful lustring n inxing. Kyphrss r xtnsivly us for inxing, tgoriztion n summrizing of oumnts. Srhing wor in th kyphrs list of oumnt inst of full ontnt rus srh tim. In ition, thy provi smnti t out ontnt of th oumnt. Unfortuntly, th grt mjority of oumnts o not hv uthor ssign kyphrss [1]. Automting kyphrs xtrtion provis nfits for mnul ssignmnt of kyphrss y inxrs. Th rmining of this ppr is strutur s follows. In stion II, It strts with short sription of wht is on prviously. Our kyphrs xtrtion lgorithm is xplin in stion III. Th rsults of xprimnts r givn in stion IV. Finlly, short isussion out our mtho n omprison with prvious mthos r provi in stion V. II. RELATED WORK Thr r svrl mthos for utomting kyphrs xtrtion in English. On th othr hn, only two mthos hv n vlop for Turkish kyphrs xtrtion. Thy r Turkish kyphrs xtrtion with KEA [2] n Turkish kyphrs xtrtor (TurKyX) [3]. Both of thm r xtn from English kyphrs xtrtion lgorithms. In [1], KEA (Kyphrs Extrtion Algorithm) hs two stgs to xtrt kyphrss: Trining stg n xtrtion stg. In th first stg, mol to intify kyphrss is rt using trining oumnts whr uthor ssign kyphrss r known. In xtrtion stg, kyphrss of nw oumnt r hosn oring to this mol. Th originl KEA uss two fturs tht r lult for h nit phrs: T F IDF (Trm Frquny Invrs Doumnt Frquny) n th istn from th ginning of th oumnt to th first ourrn of th nit phrs. KEA uss Nïv Bys thniqu to lrn two sts of numri wights from th isrtiz ftur vlus. Th mol rt in trining stg trmins th ovrll proility tht h nit is kyphrs. Finlly, nit phrss r rnk oring to this proility vlu n th ons with highr proility r rturn s kyphrss of th oumnt. In [2], KEA is opt for Turkish kyphrs xtrtion. Th iffrn with th originl KEA is using Turkish stmmr n stopwor list inst of English ountrprts. Furthrmor, nw ftur is to th lgorithm. Th nw ftur is rltiv lngth, lult s th numr of hrtrs in th phrs ivi y th lngth of th longst nit phrs. Anothr kyphrs xtrtion mtho ll B&C is propos y Brkr n Cornhi in [4]. B&C uss noun phrs hs to xtrt oumnt kyphrss. B&C xploits sttistis of noun phrss, noun phrs hs n noun phrs lngths. In ontrst with KEA, it os not n trining orpus. B&C slts top N h nouns oring to thir frqunis. For h h noun, ll noun phrss tht ontin sm wor s its h r ollt. Eh noun phrs is ssign sor lult s th prout of its frquny n lngth. K high sor phrss r slt s th kyphrss of th oumnt. In [3], th pproh of TurKyX to xtrt Turkish kyphrss is quit similr to B&C s. Th iffrn is tht TurKyX mtho uss sttistis of noun phrss n noun phrs hs. Morovr, TurKyX lso orrows som fturs omput in KEA n Turny s GnEx [5]. Our mtho is mor similr to TurKyX thn KEA in th sns tht it os not rquir trining t so th prformn os not pn on th orpor us. In ition, most of th fturs in our mtho wr lso us in TurKyX. Howvr, th rnking strtgis of two mthos in xtrtion phs r iffrnt. III. EXTRACTING KEYPHRASES USING MULTI-CRITERION RANKING Our kyphrs xtrtion thniqu onsists of two stgs. In th first stg, nit phrss r xtrt from oumnts n fturs r lult for h nit phrs. In th son stg, Hss igrm is rt from th st

2 of nit phrss. Finlly, n optiml st of kyphrss is slt using th rnking mtho sri in [6]. A. Slting Cnit Phrss W slt nit phrss in similr wy us in [3]. W onsir vry noun phrs in th oumnt s nit phrs. To intify noun phrss, w mploy suprvis Turkish prt of sph tggr (POS) [7]. Th tggr rturns most possil POS tg for h tokn (wor, puntution t) in th oumnt. Th tggr lso provis morphologil nlysis of h wor. W us ths nlyss for stmming. Nxt stp is to fin noun phrss using POS tgs. Noun phrss onsist of on h noun n zro or mor prmoifying jtivs or nouns [4]. A su-phrs of noun phrs n lso noun phrs. For this rson, h suphrs is onsir s iffrnt nit. As mntion in [3], this mtho is not n il NP-Chunkr. Mny phrss intifi y this mtho r not ligil for ing kyphrs. Thrfor, svrl filtrs r us to ru th numr of nit phrss. First filtr is out stopwors. W us list of 112 stopwors [8]. It is lso us in KEA n TurKyX. If phrs strts or ns with stopwor, it will rmov from th list of nits. Anothr filtr limits th numr of wors in nit phrs. In our implmnttion, w limint phrss whih onsist of mor thn fiv wors. In ition, w rmov phrss tht inlus wor hving only on or two hrtrs n not rogniz y oth morphologil nlyzr in [7] n Zmrk [9]. Lst two filtrs r s on n-grm pproh n rquir stm-s frquny nlysis of phrss. A noun phrs n omintion of noun phrss lik α = β 1 β k, for k 2 whr α n β i r noun phrss for 1 i k. As xpt, α n its su-phrs, β i, shoul in th nit list. Our im is to trmin most suitl nits from suh omintion. Our first frquny filtr limints su-phrss of suitl nit. Th frquny of phrs is qul or lss thn th frquny of its su-phrs. Howvr, th rtio of phrs frquny to su-phrs frquny shoul high if th phrs is mor suitl nit thn its su-phrs. For vry omintion α, w rmov its su-phrs β i from th list if f(α) f(β i ) > T high, for 1 i k (1) whr f( ) nots stm-s frquny of its rgumnt. Anothr s is tht suitl nit n our nxt to nothr noun phrs in oumnt. In suh onition, th rtio of frqunis shoul low. For vry omintion α, w rmov th phrs α from th list if i, f(α) f(β i ) < T low, for 1 i k. (2) In our implmnttion, th vlus of T high n T low r trmin mpirilly s 0.5 n 0.1, rsptivly. B. Ftur Clultion Th fturs us in our lgorithm r wll-known fturs us in vrious kyphrs xtrtion lgorithms. Six fturs r lult for h nit phrs. Thy r isprsion, first ourrn, h noun first ourrn, phrs lngth, frquny n h noun frquny. Th first on is orrow from [10], n th othrs r similr to th fturs in [3]. In omputtion of ll fturs, omprison of wors is sinsnsitiv n stm-s. 1) Disprsion: In [11], msur is vlop for th onnstion of th trm ovr txtul units. Contnt-ring trms hv tnny to lustr or lump. If trm is lustr, fwr txtul units woul ontin th trm. Th msur is s on th iffrns in proility of fining ontnt-ring phrs n not ontnt-ring phrs in txtul unit. Th xpt numr of oumnts ontining th phrs n foun s E = D [ 1 ( 1 1 ) ] T D whr D is th numr of oumnts in th orpus, n T is th totl numr of ourrns of th phrs. Connstion lustring of th phrs is fin s M = N (4) E whr N is numr of oumnts tht tully ontin th phrs. Th isprsion woul on if th phrs is rnomly istriut ovr oumnts. Th isprsion woul lss thn on if it is lustr. 2) First Ourrn: First ourrn ftur is th numr of wors tht pr th phrss first pprn. 3) H Noun First Ourrn: H noun first ourrn ftur is th numr of wors tht pr th first pprn of th phrss h noun. 4) Phrs Lngth: Phrs lngth is th numr of wors in th phrs. 5) Frquny: Th frquny of th phrs in th oumnt. 6) H Noun Frquny: Th frquny of th h noun of th phrs in th oumnt. C. Multi-Critrion Rnking Rnking with Hss Digrms is known mtho in sttistis [6]. Howvr, it hs not n us in kyphrs xtrtion yt. Gnrl pproh for rnking ojts is to omin ll fturs into on msur n sort thm with rspt to this msur. This mtho is us in [3]. Th prolm of omining msurs into on msur is to trmin wights of msurs. Anothr pproh for rnking ojts is to us prtilly orr sts (posts) sri in [6]. 1) Prtilly Orr Sts n Hss Digrm: Th nit phrss will not y,,,... t. Th im is to mk omprtiv sttmnts out two givn nit phrss n oring to thir ftur vlus (I 1, I 2,..., I 6 ) n (I 1, I 2,..., I 6) rsptivly. If I j I j (3) 2

3 Post A Post B Post C Fig. 1. f Hss igrms for two iffrnt posts. for ll j, thn is intrinsilly ttr or iggr thn, n w writ. In th s of post, w writ < if ut. On furthr rltion rquir for rnking in post is ovring rltion. Cnit phrs ovrs nit phrs if < n thr is no nit phrs x for whih < x <. W writ whn ovrs. Hss Digrm is wy of prsnting posts. A point (or vrtx) is plott for h nit phrs. Cnit phrs is lot highr on th ppr thn whnvr <. Th vrtis n r onnt y stright lin sgmnt (n g) whnvr. Hss igrms for two iffrnt posts n sn in Figur 1. Covring rltions in Post B r,, f, n f. If w try to sort th vrtis in Post A in Figur 1, possil rnks of vrtx is only 1 n possil rnks of vrtx is only 4. On th othr hn, possil rnks of vrtis n r 2 n 3. Thus, thr r two possil rnkings:,,, n,,,. In th post litrtur, rnkings r ll linr xtnsions of post. W n us th proility of possil rnks in orr to sort post. Rnk-intrvl of phrs n omput using its uppr n lowr sts. Givn S s st of lmnts, thn th uppr st of lmnt S is fin s Similrly, th lowr st is fin s U = {x S : x > } (5) L = {x S : x < } (6) Th rnk intrvl of lmnt n fin s U + 1 r S L (7) whr thr is rnking tht ssigns rnk r to lmnt. Th olltion of ll linr xtnsions of S is not s Ω. Th st Ω is finit ut gnrlly vry lrg. Mmrs of Ω r not y th symol ω, n th rnk whih ω ssigns to S is writtn s ω(). Th rnk-frquny istriution of lmnt is givn y f (r) = #{ω Ω : ω() = r} (8) n orrsponing umultiv rnk-frquny (CRF) istriution oms F (r) = f (1) + f (2) + + f (r) = #{ω Ω : ω() r}. (9) Fig. 2. Hss igrm for Post C n its linr xtnsion ision tr. Post C n its linr xtnsions ision tr r givn in Figur 2. Thr r six linr xtnsions of Post C n thr of thm ssign rnk 1 to lmnt, nottionlly f (1) = 3. Similrly, f (2) = 2 n f (3) = 1. Ptil n Tilli propos CRF oprtor for linrizing post [6]. Th oprtor uss umultiv rnk-frquny istriutions s nw initor vlus n rts nw post from th originl on. This oprtion is ppli itrtivly until th post oms linr. In othr wors, th finl post hs only on linr xtnsion tht givs th rnking of ojts. Th numr of linr xtnsions of post inrss with ftoril omplxity whn th numr of ojts in th post inrss. As rsult, numrting ll linr xtnsions of iggr posts oms omputtionlly impossil [6]. For iggr posts, Ptil n Tilli propos Mrkov Chin Mont Crlo (MCMC) smpling [6]. 2) Implmnttion Dtils: For h initor vlu, highr vlus shoul imply highr possiility to kyphrs. For this rson, w ngt th vlus of isprsion, first ourrn, h noun first ourrn n phrs lngth. Furthrmor, thr xists n xptionl s for phrs lngth. Phrss onsisting of lss numr of wors r gnrlly mor prfrr s kyphrss y uthors. Howvr, two-wor phrss r mor prfrr thn on-wor phrss [12]. For this xptionl s, phrs lngth of two-wor phrss is onsir s on n phrs lngth of on-wor phrss is onsir s two in th implmnttion. In xprimnts of our kyphrs xtrtion lgorithm, posts of nit phrss r usully ig posts. Thrfor, w first ru th numr of nit phrss y slting t most fifty nit phrss oring to th mipoints of thir rnk-intrvls. Aftrwrs, w pply MCMC smpling thniqu in linriztion of th posts. Finlly, first tn phrss in th sort list of th post r offr to usr s kyphrss of th oumnt. A. Corpor IV. EXPERIMENTS Two iffrnt orpor r us for xprimnts. First on is olltion of Turkish sintifi pprs otin from th onlin rhivs of Journl of Th Fulty of Enginring n 3

4 TABLE I SAMPLE KEYPHRASE EXTRACTION FOR GAZI UNIV. JOURNAL CORPUS TABLE III SAMPLE KEYPHRASE EXTRACTION FOR NEWS CORPUS Author Assign Author Assign İmlt Hürsi Uzmn Sistmlr Esnk İmlt Sistmlri Ypy Zk Uzmn Sistm İmlt Hürsi Root Tzgh İşlm Sırlmsı Uzmn Sistmin İmlt Sistmi Mkinn Algoritmlr Boşltm Tony Blir Ktolik Kilissi Eski İngiltr Bşknı Tony Blir Ktolik Ktolik Kilissin Byn Blir Yılın Kilis Sistmi Blir Bşkn İngiltr İşçi Prtisi TABLE II PERFORMANCE RESULT FOR GAZI UNIV. JOURNAL CORPUS TABLE IV PERFORMANCE RESULT FOR NEWS CORPUS Numr of Extrt Phrss Avrg Numr of Mths Avg. Numr of Author Assign Kyphrss Numr of Extrt Phrss Avrg Numr of Mths Avg. Numr of Author Assign Kyphrss TurKyX TurKyX KEA-TR prformn rsult is shown in Tl IV. All oumnts in th nws orpus r us in tsting for oth lgorithms. Arhittur of Gzi Univrsity. Th orpus ws rt y Pl [2]. Th orpus onsists of 60 pprs in txt formt n thir uthor-ssign kyphrss. Son orpus is olltion of nws rtils tkn from th w pgs of nwspprs n nws portls. Thr r totlly 30 nws rtils. This orpus ws rt y Klyilr [3]. B. Prformn Evlution Our lgorithm rturns 10 phrss s kyphrss of th oumnt (Tl I n Tl III). Phrss writtn in itli mth with uthor ssign kyphrss, or thy r onsir s sm. Prtilly mth phrss r not trt s orrt mth xpt tht thy rfr to sm prson; suh s Krimov for Islm Krimov. In ition, ronym of kyphrs is lso onsir s orrt mth. Smpl rsults of kyphrs xtrtion using multi-ritrion rnking () for Gzi Univrsity Journl orpus n sn in Tl I. Prformn omprison of with TurKyX [3] n Turkish Kyphrs Extrtion with KEA (KEA-TR) [2] for Gzi Univrsity Journl rtils is givn in Tl II. Prformn of lgorithms is givn for th first 5 n 10 phrss xtrt y th lgorithm. All oumnts in Gzi Univrsity Journl orpus r us in tsting for n TurKyX lgorithms. On th othr hn, 50 oumnts r us in trining n only 10 oumnts r us in tsting for KEA-TR lgorithm. Similr omprison is m for nws orpus. Smpl kyphrs xtrtion for nws orpus is givn in Tl III n V. CONCLUSION AND FUTURE WORK W propos mtho for utomting kyphrs xtrtion using multi-ritrion rnking. As sn in Tl II n Tl IV, our mtho outprforms TurKyX in oth orpor. In ition, th prformn of our mtho is vry los to KEA-TR. Howvr, th prformn of KEA-TR mtho pns on trining orpus. On th othr hn, our mtho os not rquir trining orpus, so th prformn os not hng rstilly from on orpus to nothr. For xmpl, th prformn of our mtho in oth orpor is qul whn fiv phrss r xtrt n th rsults r vry los for xtrt tn phrss. W vlop mtho for Turkish kyphrs xtrtion. Howvr, th mtho is suitl for xtning to lngugs othr thn Turkish. Using ountrprts for morphologil nlyzr, prt of sph tggr n stopwor list is suffiint for xtnsion. W xpt tht using rlil NP-Chunkr inrss prformn onsirly. Furthrmor, w think tht ing smnti fturs lik no gr in KEA++ [12] my nhn th prformn. ACKNOWLEDGMENTS This work is prtilly support y Th Sintifi n Thnil Counil of Turky Grnt TUBITAK EEEAG-107E151. REFERENCES [1] I. Wittn, G. Pyntr, E. Frnk, C. Gutwin, n C. Nvill-mnning, K: Prtil utomti kyphrs xtrtion, in Proings of Digitl Lirris 99 (DL 99), F 1999, pp

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