J Biomed Inform - On the query reformulation technique for effective MEDLINE document retrieval.

Tópicos

{ search(2224) databas(1162) retriev(909) }
{ detect(2391) sensit(1101) algorithm(908) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ control(1307) perform(991) simul(935) }
{ system(1050) medic(1026) inform(1018) }
{ extract(1171) text(1153) clinic(932) }
{ method(2212) result(1239) propos(1039) }
{ imag(1057) registr(996) error(939) }
{ network(2748) neural(1063) input(814) }
{ problem(2511) optim(1539) algorithm(950) }
{ research(1085) discuss(1038) issu(1018) }
{ patient(2837) hospit(1953) medic(668) }
{ group(2977) signific(1463) compar(1072) }
{ activ(1452) weight(1219) physic(1104) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ method(1219) similar(1157) match(930) }
{ patient(2315) diseas(1263) diabet(1191) }
{ take(945) account(800) differ(722) }
{ studi(2440) review(1878) systemat(933) }
{ framework(1458) process(801) describ(734) }
{ error(1145) method(1030) estim(1020) }
{ concept(1167) ontolog(924) domain(897) }
{ method(1557) propos(1049) approach(1037) }
{ design(1359) user(1324) use(1319) }
{ model(2220) cell(1177) simul(1124) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ spatial(1525) area(1432) region(1030) }
{ ehr(2073) health(1662) electron(1139) }
{ age(1611) year(1155) adult(843) }
{ cost(1906) reduc(1198) effect(832) }
{ gene(2352) biolog(1181) express(1162) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ high(1669) rate(1365) level(1280) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ measur(2081) correl(1212) valu(896) }
{ bind(1733) structur(1185) ligand(1036) }
{ sequenc(1873) structur(1644) protein(1328) }
{ featur(3375) classif(2383) classifi(1994) }
{ imag(2830) propos(1344) filter(1198) }
{ imag(2675) segment(2577) method(1081) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ clinic(1479) use(1117) guidelin(835) }
{ algorithm(1844) comput(1787) effici(935) }
{ data(1714) softwar(1251) tool(1186) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ featur(1941) imag(1645) propos(1176) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ import(1318) role(1303) understand(862) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ blood(1257) pressur(1144) flow(957) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ sampl(1606) size(1419) use(1276) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ can(981) present(881) function(850) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ method(1969) cluster(1462) data(1082) }

Resumo

Improving the retrieval accuracy of MEDLINE documents is still a challenging issue due to low retrieval precision. Focusing on a query expansion technique based on pseudo-relevance feedback (PRF), this paper addresses the problem by systematically examining the effects of expansion term selection and adjustment of the term weights of the expanded query using a set of MEDLINE test documents called OHSUMED. Implementing a baseline information retrieval system based on the Okapi BM25 retrieval model, we compared six well-known term ranking algorithms for useful expansion term selection and then compared traditional term reweighting algorithms with our new variant of the standard Rocchio's feedback formula, which adopts a group-based weighting scheme. Our experimental results on the OHSUMED test collection showed a maximum improvement of 20.2% and 20.4% for mean average precision and recall measures over unexpanded queries when terms were expanded using a co-occurrence analysis-based term ranking algorithm in conjunction with our term reweighting algorithm (p-value<0.05). Our study shows the behaviors of different query reformulation techniques that can be utilized for more effective MEDLINE document retrieval.

Resumo Limpo

improv retriev accuraci medlin document still challeng issu due low retriev precis focus queri expans techniqu base pseudorelev feedback prf paper address problem systemat examin effect expans term select adjust term weight expand queri use set medlin test document call ohsum implement baselin inform retriev system base okapi bm retriev model compar six wellknown term rank algorithm use expans term select compar tradit term reweight algorithm new variant standard rocchio feedback formula adopt groupbas weight scheme experiment result ohsum test collect show maximum improv mean averag precis recal measur unexpand queri term expand use cooccurr analysisbas term rank algorithm conjunct term reweight algorithm pvalu studi show behavior differ queri reformul techniqu can util effect medlin document retriev

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