| Inputs: Source ontology (SO) and Target ontology (TO) |
| Outputs: Alignments (A) |
| Variables:ik |
| hashmap<(length, prefix), ID>//save length and prefix of entities in SO and TO |
| typicalList < IDeso, IDeto>//save typical entities in SO and TO |
| blockSetSO//save the set of blocks of SO |
| blockSetTO//save the set of blocks of TO |
| subOntoSetSO//save the set of sub-ontologies of SO |
| subOntoSetTO//save the set of sub-ontologies of TO |
| (1) | //Step 1: generate typical entities |
| (2) | for entity ei in SO, TO: |
| (3) | length = number of letters in label of ei |
| (4) | prefix = prefix of label of ei |
| (5) | hashmap.put(length, prefix, IDei) |
| (6) | end for |
| (7) | for key (length, prefix) in hashmap: |
| (8) | for IDs in values (IDe1, IDe2, …, IDen): |
| (9) | if simT(IDei, IDej) > threshold and IDei ∈ SO and IDej ∈ TO://simT is shown in formula (2) |
| (10) | typicalList.add(IDei, IDej) |
| (11) | end if |
| (12) | end for |
| (13) | end for |
| (14) | //Step 2: clustering typical entities |
| (15) | for every entities IDeso, IDeto in typicalList < IDeso, IDeto>: |
| (16) | setSO.add(IDeso), setTO.add(IDeto) |
| (17) | blockSetSO = partition(setSO), blockSetTO = partition(setTO)//partition is shown in [15]. |
| (18) | end for |
| (19) | //Step 3: partitioning/merging blocks |
| (20) | for every entity sets Si in blockSetSO: |
| (21) | for every entities IDeso[k] in Si: |
| (22) | tempEntity = typicalList.get(indexOf(IDeso[k])).get(1) |
| (23) | if k = 0: |
| (24) | //correSet records the corresponding setTO in blockSetTO |
| (25) | correSet = setTO which contains tempEntity in blockSetTO |
| (26) | else if tempEntity is not in correSet: |
| (27) | //sourceSet records the corresponding setSO in blocksSetSO |
| (28) | sourceSet = setSO which contains tempEntity in blockSetSO |
| (29) | correSet.add(tempEntity) |
| (30) | sourceSet.delete(tempEntity) |
| (31) | end if |
| (32) | end for |
| (33) | end for |
| (34) | //Step 4: extracting sub-ontologies |
| (35) | for every entity sets Si in blockSetSO, blockSetTO: |
| (36) | do: |
| (37) | n = Si.size |
| (38) | tempSet = null |
| (39) | //rH, rC, ek is shown as formula (3)∼(8) |
| (40) | for every entities IDeso[k] in Si: |
| (41) | candidateEntity = IDeso[k].get(rdfs:sub-ClassOf) |
| (42) | if rH(candidateEntity, IDeso) > threshold: |
| (43) | tempSet.add(candidateEntity) |
| (44) | candidateEntity = IDeso[k].get(rdfs: hasSomeValueFrom) |
| (45) | if rC(candidateEntity, IDeso) > threshold: |
| (46) | tempSet.add(candidateEntity) |
| (47) | update extension factor ek |
| (48) | end for |
| (49) | Si.add(tempSet) |
| (50) | while(Si.size ! = n) |
| (51) | end for |
| (52) | subOntoSetSO = blockSetSO |
| (53) | subOntoSetTO = blockSetTO |
| (54) | //Step 5: matching sub-ontologies |
| (55) | for every pair sub-ontologies (subSO[i], subTO[i]) in subOntoSetSO, subOntoSetTO: |
| (56) | //matchStruc by V-DOC in [18]. |
| (57) | structureAlignment = matchStruc(subSO[i], subTO[i]) |
| (58) | //matchSema by GMO in [19]. |
| (59) | sematicAlignment = matchSema(subSO[i], subTO[i], structureAlignment) |
| (60) | A.add(structureAlignment), A.add(sematicAlignment) |
| (61) | end for |
