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| "paper_id": "O08-2008", | |
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| "date_generated": "2023-01-19T08:02:38.067157Z" | |
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| "title": "Conceptual Expansion and Ontological Mapping of Multi-domain Documents", | |
| "authors": [ | |
| { | |
| "first": "Yong-Xiang", | |
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| "first": "Xiu-Ling", | |
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| { | |
| "first": "Chu-Ren", | |
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| "bib_entries": { | |
| "BIBREF0": { | |
| "ref_id": "b0", | |
| "title": "Combining local context and WordNet sense similiarity for word sense disambiguation", | |
| "authors": [ | |
| { | |
| "first": "C", | |
| "middle": [], | |
| "last": "Leacock", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "M", | |
| "middle": [], | |
| "last": "Chodorow", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 1998, | |
| "venue": "WordNet, An Electronic Lexical Database", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "C. Leacock and M. Chodorow, \"Combining local context and WordNet sense similiarity for word sense disambiguation,\" In WordNet, An Electronic Lexical Database. The MIT Press, 1998.", | |
| "links": null | |
| }, | |
| "BIBREF1": { | |
| "ref_id": "b1", | |
| "title": "Using information content to evaluate semantic similarity", | |
| "authors": [ | |
| { | |
| "first": "P", | |
| "middle": [], | |
| "last": "Resnik", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 1995, | |
| "venue": "Proceedings of the 14th International Joint Conference on Artificial Intelligence", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "P. Resnik, \"Using information content to evaluate semantic similarity,\" In Proceedings of the 14th International Joint Conference on Artificial Intelligence, Montreal, Canada, 1995.", | |
| "links": null | |
| }, | |
| "BIBREF2": { | |
| "ref_id": "b2", | |
| "title": "An information-theoretic definition of similarity", | |
| "authors": [ | |
| { | |
| "first": "D", | |
| "middle": [], | |
| "last": "Lin", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 1998, | |
| "venue": "Proceedings of the 15th International Conference on Machine Learning", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "D. Lin, \"An information-theoretic definition of similarity,\" In Proceedings of the 15th International Conference on Machine Learning, Madison, WI, 1998.", | |
| "links": null | |
| }, | |
| "BIBREF3": { | |
| "ref_id": "b3", | |
| "title": "An Expert System for Automatic Query Reformation", | |
| "authors": [ | |
| { | |
| "first": "S", | |
| "middle": [], | |
| "last": "Gauch", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "J", | |
| "middle": [ | |
| "B" | |
| ], | |
| "last": "Smith", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 1993, | |
| "venue": "Journal of the American Society for Information Science", | |
| "volume": "44", | |
| "issue": "3", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "S. Gauch and J. B. Smith, \"An Expert System for Automatic Query Reformation,\" Journal of the American Society for Information Science, vol. 44, no.3, 1993.", | |
| "links": null | |
| }, | |
| "BIBREF4": { | |
| "ref_id": "b4", | |
| "title": "A Concept Space Approach to Addressing the Vocabulary Problem in Scientific Information Retrieval: An Experiment on the Worm Community System", | |
| "authors": [ | |
| { | |
| "first": "H", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "T", | |
| "middle": [ | |
| "D" | |
| ], | |
| "last": "Ng", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "J", | |
| "middle": [], | |
| "last": "Martinez", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "B", | |
| "middle": [ | |
| "R" | |
| ], | |
| "last": "Schatz", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 1997, | |
| "venue": "Journal of the American Society for Information Science", | |
| "volume": "48", | |
| "issue": "1", | |
| "pages": "17--31", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "H. Chen, T. D. Ng, J. Martinez, and B. R. Schatz, \"A Concept Space Approach to Addressing the Vocabulary Problem in Scientific Information Retrieval: An Experiment on the Worm Community System,\" Journal of the American Society for Information Science, vol. 48, no.1, pp.17-31, 1997.", | |
| "links": null | |
| }, | |
| "BIBREF6": { | |
| "ref_id": "b6", | |
| "title": "Toward a Standard Upper Ontology", | |
| "authors": [ | |
| { | |
| "first": "I", | |
| "middle": [], | |
| "last": "Niles", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "A", | |
| "middle": [], | |
| "last": "Pease", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2001, | |
| "venue": "Proceedings of the 2nd International Conference on Formal Ontology in Information Systems (FOIS-2001)", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "I. Niles and A. Pease, \"Toward a Standard Upper Ontology,\" In Proceedings of the 2nd International Conference on Formal Ontology in Information Systems (FOIS-2001), Chris Welty and Barry Smith, eds, Ogunquit, Maine, 2001.", | |
| "links": null | |
| }, | |
| "BIBREF7": { | |
| "ref_id": "b7", | |
| "title": "\u4e2d\u592e\u7814\u7a76\u9662\u4e2d\u82f1\u96d9\u8a9e\u77e5\uf9fc\u672c\u9ad4\u8a5e\u7db2 The Academia Sinica Bilingual Ontological Wordnet", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "\u4e2d\u592e\u7814\u7a76\u9662\u4e2d\u82f1\u96d9\u8a9e\u77e5\uf9fc\u672c\u9ad4\u8a5e\u7db2 The Academia Sinica Bilingual Ontological Wordnet (Sinica BOW)\uff0chttp://BOW.sinica.edu.tw", | |
| "links": null | |
| }, | |
| "BIBREF9": { | |
| "ref_id": "b9", | |
| "title": "Cross-lingual Portability ofSemantic relations: Bootstrapping Chinese WordNet with English WordNet Relations", | |
| "authors": [ | |
| { | |
| "first": "C", | |
| "middle": [ | |
| "R" | |
| ], | |
| "last": "Huang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "E", | |
| "middle": [ | |
| "I J" | |
| ], | |
| "last": "Tseng", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "D", | |
| "middle": [ | |
| "B S" | |
| ], | |
| "last": "Tsai", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "B", | |
| "middle": [], | |
| "last": "Murphy", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2003, | |
| "venue": "Language and Linguistics", | |
| "volume": "4", | |
| "issue": "", | |
| "pages": "509--532", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "C. R. Huang, E. I. J. Tseng, D. B. S. Tsai, and B. Murphy, \"Cross-lingual Portability ofSemantic relations: Bootstrapping Chinese WordNet with English WordNet Relations,\" Language and Linguistics, vol. 4.3, pp. 509-532, 2003.", | |
| "links": null | |
| }, | |
| "BIBREF10": { | |
| "ref_id": "b10", | |
| "title": "Sinica BOW (Bilingual Ontological Wordnet): Integration of Bilingual WordNet and SUMO", | |
| "authors": [ | |
| { | |
| "first": "C", | |
| "middle": [ | |
| "R" | |
| ], | |
| "last": "Huang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "R", | |
| "middle": [ | |
| "Y" | |
| ], | |
| "last": "Chang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "S", | |
| "middle": [ | |
| "B" | |
| ], | |
| "last": "Lee", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2004, | |
| "venue": "4th International Conference on Language Resources and Evaluation (LREC2004)", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "C. R. Huang, R. Y. Chang, and S. B. Lee, \"Sinica BOW (Bilingual Ontological Wordnet): Integration of Bilingual WordNet and SUMO,\" 4th International Conference on Language Resources and Evaluation (LREC2004), Lisbon. Portugal, 2004.", | |
| "links": null | |
| }, | |
| "BIBREF11": { | |
| "ref_id": "b11", | |
| "title": "Introduction to CKIP Chinese Word Segmentation System for the First International Chinese Word Segmentation Bakeoff", | |
| "authors": [ | |
| { | |
| "first": "W", | |
| "middle": [ | |
| "Y" | |
| ], | |
| "last": "Ma", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "K", | |
| "middle": [ | |
| "J" | |
| ], | |
| "last": "Chen", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2003, | |
| "venue": "Proceedings of ACL, Second SIGHAN Workshop on Chinese Language Processing", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "168--171", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "W. Y. Ma and K. J. Chen, \"Introduction to CKIP Chinese Word Segmentation System for the First International Chinese Word Segmentation Bakeoff,\" Proceedings of ACL, Second SIGHAN Workshop on Chinese Language Processing, pp. 168-171, 2003.", | |
| "links": null | |
| }, | |
| "BIBREF12": { | |
| "ref_id": "b12", | |
| "title": "A Bottom-up Merging Algorithm for Chinese Unknown Word Extraction", | |
| "authors": [ | |
| { | |
| "first": "W", | |
| "middle": [ | |
| "Y" | |
| ], | |
| "last": "Ma", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "K", | |
| "middle": [ | |
| "J" | |
| ], | |
| "last": "Chen", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2003, | |
| "venue": "Proceedings of ACL, Second SIGHAN Workshop on Chinese Language Processing", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "31--38", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "W. Y. Ma and K. J. Chen, \"A Bottom-up Merging Algorithm for Chinese Unknown Word Extraction,\" Proceedings of ACL, Second SIGHAN Workshop on Chinese Language Processing, pp. 31-38, 2003.", | |
| "links": null | |
| } | |
| }, | |
| "ref_entries": { | |
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\u7684\u6210\u679c\u67e5\u8a62\u4ecb\u9762\u63d0\u4f9b\u5404\u754c\u4f7f\u7528\u8005\u67e5\u8a62\u61c9\u7528\uff0c\u5206\u5225\u70ba\u806f\u5408\u76ee\u9304\u53ca\u516c\u5171\u5c55\u793a\u7cfb\u7d71\u3002 \u900f\u904e\u77e5\u8b58\u672c\u9ad4\u7684\u7d50\u69cb\u7cfb\u7d71\uff0c\u53ef\u4ee5\u6bd4\u8f03\u56b4\u8b39\u7684\u5c07\u77e5\u8b58\u7d50\u69cb\u7cfb\u7d71\u5efa\u7acb\u8d77\u4f86\uff0c\u672c\u7814\u7a76\u5373\u4ee5 \u6578\u4f4d\u5178\u85cf\u570b\u5bb6\u578b\u79d1\u6280\u8a08\u756b\u6240\u63d0\u4f9b\u4e4b 39,765 \u7acb\u7684\u4e2d\u6587\u8a5e\u7fa9\u5206\u6790\u8207\u77e5\u8b58\u672c\u9ad4\u67b6\u69cb\uff0c\u5c07\u6a19\u984c\u8a5e\u5f59\u5c0d\u61c9\u81f3 SUMO ontology \u7bc0\u9ede\u4e0a\u9032\u884c\u6982 \u5ff5\u64f4\u5c55\u8207\u7fa4\u96c6\uff0c\u518d\u4ee5\u4e2d\u6587\u69cb\u8a5e\u6a23\u5f0f\u70ba\u6a19\u6e96\u9032\u884c\u7fa4\u96c6\u7e2e\u6e1b\uff0c\u4ee5\u8a5e\u5f59\u8a9e\u7fa9\u5206\u6790\u65b9\u5f0f\u63d0\u4f9b\u7279\u6b8a \u9818\u57df\u5178\u85cf\u8cc7\u6599\u5eab\u4e2d\u8cc7\u8a0a\u6aa2\u7d22\u53ef\u884c\u4e4b\u65b9\u6848\u3002 \u4e8c\u3001\u76f8\u95dc\u7814\u7a76 (\u4e00) \u8a9e\u7fa9\u76f8\u4f3c\u5ea6\u8207\u67e5\u8a62\u64f4\u5c55 \u8ddd\u96e2\u5c0e\u5411\u7684\u76f8\u4f3c\u5ea6\u65b9\u6cd5\u662f\u5f9e\u5927\u7684\u6587\u5b57\u8a9e\u6599\u5eab\u4e2d\u53bb\u5b78\u51fa\u5206\u5e03\u7684\u76f8\u4f3c\u5ea6\u4f86\u5efa\u7acb\u6a21\u578b\uff0c Leacock & Chodorow [1]\uff0cResnik [2]\uff0cLin [3]\u6240\u63d0\u51fa\u7684\u662f\u4e09\u7a2e\u5728\u81ea\u7136\u8a9e\u8a00\u8655\u7406\u61c9\u7528\u4e0a\u5f88 \u6a19\u6e96\u7684\u65b9\u6cd5\u3002\u9019\u4e9b\u516c\u5f0f\u90fd\u662f\u5b9a\u7fa9\u7528\u4f86\u6e2c\u91cf\u6982\u5ff5(Concept)\u4e0a\u7684\u76f8\u4f3c\u5ea6, \u800c\u975e\u8a5e\u5f59(word)\u4e0a \u4e00\u822c\u8cc7\u8a0a\u7684\u6aa2\u7d22\u662f\u7528\u8a5e\u5f59\u4f86\u4ee3\u8868\u6982\u5ff5\u3002\u4f46\u6982\u5ff5\u8207\u8a5e\u5f59\u7684\u95dc\u4fc2\u4e26\u975e\u90fd\u662f\u4e00\u5c0d\u4e00\u7684\uff0c\u5982 \u540c\u7fa9\u8a5e(Synonym)\u7528\u4f86\u8868\u793a\u591a\u500b\u8a5e\u5f59\u90fd\u5177\u6709\u76f8\u540c\u7684\u6982\u5ff5\uff0c\u5373\u4e00\u500b\u6982\u5ff5\u53ef\u5c0d\u61c9\u5230\u591a\u500b\u8a5e \u5f59\u3002\u56e0\u6b64\uff0c\u5728\u6aa2\u7d22\u6642\u82e5\u80fd\u5efa\u69cb\u6982\u5ff5\u8207\u8a5e\u5f59\u9593\u7684\u660e\u78ba\u95dc\u4fc2\uff0c\u5c07\u6709\u6548\u63d0\u5347\u6aa2\u7d22\u6548\u76ca\u3002\u5728\u4e00\u822c \u641c\u5c0b\u5f15\u64ce\u7684\u8a2d\u8a08\u4e0a\uff0c\u6700\u5e38\u898b\u7684\u7b56\u7565\u662f\u5229\u7528\u8a5e\u5f62\u6bd4\u5c0d\u7684\u65b9\u5f0f\u4f5c\u70ba\u8cc7\u8a0a\u6aa2\u7d22\u7684\u57fa\u672c\u65b9\u6cd5\uff0c\u518d \u8f14\u52a9\u4ee5\u5404\u7a2e\u7684\u67e5\u8a62\u8a5e\u5f59\u64f4\u5c55\u6216\u662f\u76f8\u95dc\u7d71\u8a08\u904b\u7b97\u7d50\u679c\u4f86\u627e\u51fa\u4f7f\u7528\u8005\u611f\u8208\u8da3\u7684\u8cc7\u6599\u3002 \u9664\u4e86\u5229\u7528\u95dc\u9375\u8a5e\u9032\u884c\u5168\u6587\u6aa2\u7d22(Full-Text Search)\u5916\uff0c\u6709\u4e9b\u8cc7\u8a0a\u6aa2\u7d22\u7cfb\u7d71\u5c1a\u91dd\u5c0d\u6587 \u4ef6\u7684\u5167\u5bb9\u9032\u884c\u5206\u6790\uff0c\u7d66\u4e88\u6587\u4ef6\u8cc7\u6599\u6aa2\u7d22\u6a19\u8b58(\u5982\u4e3b\u984c\u8a5e\u5f59\u6216\u5206\u985e\u865f)\uff0c\u4e26\u4f7f\u7528\u7d22\u5f15\u8a5e\u5f59 \u4f86\u8868\u793a\u6587\u4ef6\u5167\u5bb9\uff0c\u8cc7\u8a0a\u4f7f\u7528\u8005\u8207\u8cc7\u8a0a\u6aa2\u7d22\u7cfb\u7d71\u4e4b\u9593\u85c9\u7531\u7d22\u5f15\u8a5e\u5f59\u8207\u6aa2\u7d22\u8a5e\u5f59\u4e4b\u9593\u7684\u5c0d\u61c9 \u4f86\u9054\u5230\u64f7\u53d6\u8207\u904e\u6ffe\u8cc7\u8a0a\u7684\u76ee\u7684\u3002\u67e5\u8a62\u554f\u53e5\u7684\u64f4\u5c55\u901a\u5e38\u4ee5\u4f7f\u7528\u8005\u63d0\u4f9b\u7684\u6aa2\u7d22\u8a5e\u5f59\u70ba\u57fa\u790e\uff0c \u7576\u539f\u59cb\u67e5\u8a62\u554f\u53e5\u7684\u6aa2\u7d22\u6548\u76ca\u4e0d\u597d\u6642\uff0c\u5247\u53ef\u4ee5\u8ffd\u52a0\u66f4\u591a\u7684\u8a5e\u5f59\u4f86\u6539\u5584\u3002\u95dc\u65bc\u67e5\u8a62\u554f\u53e5\u7684\u64f4 \u5c55\uff0c\u5c1a\u6709\u76f8\u95dc\u7814\u7a76\u63d0\u51fa\u5229\u7528\u76f8\u95dc\u56de\u994b (Relevance Feedback) \u6216\u662f\u4f7f\u7528\u77e5\u8b58\u67b6\u69cb (Ontology) \u7684\u5143\u77e5\u8b58(Atom Knowledge)\u4f86\u9032\u884c[4]\u3002Stiles \u662f\u6700\u65e9\u63d0\u51fa\u5229\u7528\u76f8\u95dc\u8a5e\u5f59\u4f86\u6539\u9032\u6aa2\u7d22\u6548 \u76ca\u7406\u8ad6\u7684\u5b78\u8005\u4e4b\u4e00[5]\u3002 (\u4e8c) \u5efa\u8b70\u4e0a\u5c64\u5171\u7528\u77e5\u8b58\u672c\u9ad4(Suggested Upper Merged Ontology\uff1bSUMO) SUMO(Suggested Upper Merged Ontology\uff0c\u5efa\u8b70\u4e0a\u5c64\u5171\u7528\u77e5\u8b58\u672c\u9ad4)[6]\u662f\u7531 IEEE \u6a19\u6e96\u4e0a\u5c64\u77e5\u8b58\u672c\u9ad4\u5de5\u4f5c\u5c0f\u7d44\u6240\u63d0\u51fa\u7684\u77e5\u8b58\u672c\u9ad4\u67b6\u69cb\uff0c\u76ee\u7684\u662f\u767c\u5c55\u6210\u6a19\u6e96\u7684\u4e0a\u5c64\u77e5\u8b58\u672c \u9ad4\uff0c\u9019\u5c07\u4fc3\u9032\u8cc7\u6599\u4e92\u901a\u6027\u3001\u8cc7\u8a0a\u641c\u5c0b\u548c\u6aa2\u7d22\u3001\u81ea\u52d5\u63a8\u7406\u548c\u81ea\u7136\u8a9e\u8a00\u8655\u7406\u3002\u77e5\u8b58\u672c\u9ad4 (ontology)\u985e\u4f3c\u65bc\u4e00\u7d44\u5b57\u5178\u6216\u8853\u8a9e\u8868\uff0c\u4f46\u80fd\u5920\u4f7f\u96fb\u8166\u8655\u7406\u66f4\u591a\u5167\u5bb9\u7684\u7d30\u7bc0\u548c\u5176\u7d50\u69cb\u3002 \u900f\u904e\u77e5\u8b58\u672c\u9ad4\u53ef\u5c07\u4eba\u5011\u6709\u8208\u8da3\u7684\u9818\u57df\u6b63\u898f\u5316\u70ba\u4e00\u5957\u6982\u5ff5\u3001\u95dc\u4fc2\u548c\u5b9a\u7406(axiom) \u3002\u4e0a\u5c64\u7684 \u77e5\u8b58\u672c\u9ad4\u88ab\u9650\u5236\u5728 meta \u7684\u6982\u5ff5\u3001\u4e00\u822c\u3001\u62bd\u8c61\u6216\u8005\u54f2\u5b78\uff0c\u56e0\u6b64\u8db3\u5920\u4e00\u822c\u63d0\u51fa(\u5728\u4e00\u5b9a\u6c34 \u6e96\u4e0a)\u4e00\u500b\u6db5\u84cb\u5ee3\u95ca\u7bc4\u570d\u7684\u9818\u57df\u5340\u57df[7]\u3002\u7279\u6b8a\u9818\u57df\u5177\u9ad4\u7684\u6982\u5ff5\u4e0d\u88ab\u5305\u62ec\u5728\u4e0a\u5c64\u77e5\u8b58\u672c \u9ad4\u4e2d\uff0c\u4f46\u662f\u9019\u6a23\u7684\u77e5\u8b58\u672c\u9ad4\u53ef\u63d0\u4f9b\u7279\u6b8a\u9818\u57df(\u4f8b\u5982\uff1a\u85e5\u3001\u8ca1\u653f\u3001\u5c08\u6848\u2026\u7b49\u7b49)\u7684\u77e5\u8b58\u672c \u9ad4\u7d50\u69cb\u7684\u5efa\u7acb\u3002SUMO \u85c9\u7531\u6700\u9ad8\u5c64\u6b21\u7684\u77e5\u8b58\u672c\u9ad4\uff0c\u9f13\u52f5\u5176\u4ed6\u7279\u6b8a\u9818\u57df\u77e5\u8b58\u672c\u9ad4\u4ee5\u5176\u70ba \u57fa\u790e\u884d\u751f\u51fa\u5176\u4ed6\u7279\u6b8a\u9818\u57df\u7684\u77e5\u8b58\u672c\u9ad4\uff0c\u4e26\u70ba\u4e00\u822c\u591a\u7528\u9014\u7684\u8853\u8a9e\u63d0\u4f9b\u5b9a\u7fa9\u3002\u76ee\u524d SUMO \u5df2\u7d93\u548c\u82f1\u8a9e\u8a5e\u5f59\u7db2\u8def WordNet1.6 \u7248\u672c\u4f5c\u521d\u6b65\u7684\u9023\u7d50\u3002SUMO \u4e2d\u7684\u7bc0\u9ede\u4ee5\u968e\u5c64\u6a39\u65b9\u5f0f\u9023 \u7d50\uff0c\u5982\u5716\u4e00\u6240\u793a\u3002 (\u4e09) \u4e2d\u592e\u7814\u7a76\u9662\u4e2d\u82f1\u96d9\u8a9e\u77e5\uf9fc\u672c\u9ad4\u8a5e\u7db2(Sinica BOW) \uf9e4\uf941\u6240\u8ff0\u7684\u4eba\uf9d0\u8a5e\u5f59\u8a18\u61b6\u70ba\u555f\u767c\u6240\u958b\u767c\u51fa\u7684\u8a9e\u610f\u5f0f\u96fb\u5b50\u5b57\u5178\uff0c\u4ee5\u6bcf\u500b\u540c\u7fa9\u8a5e\u96c6\u8868\u9054\u4e00\u7a2e \u8a5e\u5f59\u6982\uf9a3\uff0c\u5c07\u540c\u7fa9\u8a5e\u96c6\u5340\u5206\u70ba\u56db\u7a2e\u82f1\u6587\u8a5e\uf9d0\uff1a\u540d\u8a5e\u3001\u52d5\u8a5e\u3001\u5f62\u5bb9\u8a5e\u3001\u526f\u8a5e\uff0c\u4e26\u4ee5\u4e8c\u5341\u5e7e \u7a2e\u8a5e\u7fa9\u95dc\u4fc2\u7d44\u7e54\u540c\u7fa9\u8a5e\u96c6\u3002\u7531\u4e2d\u7814\u9662\u8cc7\u8a0a\u6240\u8207\u8a9e\u8a00\u6240\u5408\u4f5c\u5efa\u69cb\u7684 ECTED \u4ee5 WordNet \u70ba\u57fa\u790e\uff0c\u7d93\u7531\u73fe\u6709\u82f1\u4e2d\u6216\u4e2d\u82f1\u96fb\u5b50\u8fad\u5178\u7684\u8a5e\u5f62\u5c0d\u61c9\uff0c\u7232\u6bcf\u500b\u540c\u7fa9\u8a5e\u96c6\u8a5e\u7fa9\u627e\u51fa\u53ef\u80fd\u76f8\u5c0d \u61c9\u7684\u4e2d\u8b6f\u8a5e\u7d44\uff0c\u518d\u7d93\u7531\u4eba\u5de5\u6aa2\u9a57\u3002\u5c0b\u627e\u5c0d\u8b6f\u76e1\u53ef\u80fd\u7684\u4ee5\u8a5e\u5f59\u800c\u975e\u63cf\u8ff0\u6027\u77ed\u8a9e\u8868\u9054\uff0c\u76ee\u7684 \u5728\u65bc\u8b93\u6bcf\u500b\u540c\u7fa9\u8a5e\u96c6\u90fd\u6709\u6700\u9069\u7576\u7684\u4e00\u81f3\u4e09\u500b\u5de6\u53f3\u7684\u4e2d\u6587\u5c0d\u8b6f\u3002[10] \u5be6\u9ad4 \u7269\u8cea\u7684 \u7269\u9ad4 \u81ea\u8eab\u9023\u7e8c\u7269\u9ad4 \u7269\u8cea \u7d14\u7269\u8cea \u57fa\u672c\u7269\u8cea \u91d1\u5c6c \u539f\u5b50 \u6b21\u539f\u5b50\u7c92\u5b50 \u539f\u5b50\u6838 \u96fb\u5b50 \u8cea\u5b50 \u4e2d\u5b50 \u5316\u5408\u7269 \u6c34 \u990a\u4efd \u5716\u4e00\u3001 SUMO\u968e\u5c64\u7bc0\u9ede\u793a\u4f8b \u4f9d\u64daSUMO 2002\uf98e\u7248\u8cc7\uf9be\uff0c\u9ec3\u5c45\u4ec1\u7b49\u4eba[11]\u5c07\u7cfb\u7d71\u4ecb\u9762\u4ee5\u53ca\u6982\uf9a3\u7bc0\u9ede\u9032\ufa08\u4e2d\u6587\u5316\u7d0d \u5165Sinica BOW\u4e4b\u4e2d\u4e26\u9032\u884c\u5c0d\u61c9\u9023\u7d50\uff0c\u5176\u6db5\u84cb11\u5927\uf9d0\u7684\u6982\uf9a3\uff0c\u6bcf\u5927\uf9d0\u53c8\u5340\u5206\u70ba\u4e8c\u81f3\u4e94\u500b\uf9d0 \u5225\uff0c\u7e3d\u5171\u56ca\u62ec3,912\u500b\u6982\uf9a3\u3002SUMO\u5df2\u7d93\u8207WordNet1.6\u7248\u672c\u7d50\u5408\uff0c\u4e14\u4ee5\u540c\u7fa9(synonymy) \u3001 \u56e0WordNet1.6 offset\u5ef6\u4f38\u7684\uf9fc\u5225\u78bc\u53ef\u7372\u5f97\u539f\u672cWordNet\u5b58\u5728\u7684\u8a5e\uf9d0\u3001\u89e3\u91cb\u3001\u82f1\u6587\uf9b5 \uf906\u3001\u540c\u7fa9\u8a5e\u96c6\u3001\u5404\u540c\u7fa9\u8a5e\u96c6\u9593\u7684\u8a5e\u7fa9\u95dc\u4fc2\u53ca\u5176\u6240\u5c6c\u8a5e\u5f59\u3002\u800cSUMO\u6982\uf9a3\u8207WordNet\u7684\uf99a \u7d50\uff0c\u4f7f\u5f97\u53ef\u900f\u904e\u8a72\uf9fc\u5225\u78bc\u7372\u53d6\u8a5e\u7fa9\u8207\u6982\uf9a3\u642d\u914d\u7684\u8a0a\u606f\u3002\u4ee5WordNet\u70ba\u57fa\u790e\u6240\u5efa\u7f6e\u7684 ECTED\u8207\u91dd\u5c0dWordNet\u540c\u7fa9\u8a5e\u96c6\u7684\u5404\u8a5e\u5f59\u9805\u76ee\u6240\u7d66\u4e88\u7684\uf9b4\u57df\u503c\uff0c\u4e5f\u662f\u900f\u904e\u8a72\uf9fc\u5225\u78bc\u7372 \u53d6\u3002\u800c\u7279\u6b8a\uf9b4\u57df\u8a5e\u5f59\u5eab\uff0c\u52a0\u4e0a\u76f8\u5c0d\u61c9\u7684Sinica BOW\uf9fc\u5225\u78bc\uff0c\u4e5f\u53ef\u4fdd\uf9cd\u539f\u59cb\u8cc7\u6e90\u7684\u8cc7\uf9be\u5eab \u683c\u5f0f\u548cWordNet\uf99a\u7d50\u3002 \u56e0\uf9b4\u57df\u77e5\uf9fc\u672c\u9ad4\u5247\u662f\u5728SUMO\u67d0\u4e9b\u6982\uf9a3\u4e0b\u9032\ufa08\u5ef6\u4f38\u767c\u5c55\u3002\u6bcf\u500b\u7279\u6b8a\uf9b4\u57df\u8a5e\u5f59\u5eab\u4e2d\u7684 \u8a5e\u5f59\u4e00\u6a23\u5177\u6709\u6240\u5c6c\u7684\u6982\uf9a3\uff0c\u5176\u6240\u5c6c\u6982\uf9a3\u53ef\u80fd\u662fSUMO\u6216\u7279\u6b8a\uf9b4\u57df\u77e5\uf9fc\u672c\u9ad4\u7684\u67d0\u4e00\u6982\uf9a3\uff0c \u7279\u6b8a\uf9b4\u57df\u8a5e\u5f59\u5eab\u548c\uf9b4\u57df\u77e5\uf9fc\u672c\u9ad4\u7684\u7d50\u5408\uff0c\u4f7f\u5f97\u900f\u904e\u8a72\uf9fc\u5225\u78bc\u53c8\uf905\u8d77\u6240\u6709\u7684\u8a0a\u606f\u3002Sinica BOW\u7684\u8cc7\u6e90\u548c\u67b6\u69cb\u5982\u5716\u4e8c\u6240\u793a\u3002\u7531\u65bc\u900f\u904eWordNet\u53ef\u4ee5\u548c\u540c\u662f\u4ee5WordNet\u70ba\u57fa\u790e\u67b6\u69cb\u6240 \u5efa\u7f6e\u7684\u5176\u4ed6\u8a9e\u7cfbWordNet\u8cc7\u6e90\u52a0\u4ee5\uf99a\u7d50\uff0c\uf9b5\u5982\uff1aEuroWordNet[7]\uff0c\u56e0\u6b64\u4ee5\u6b64\u57fa\u790e\u67b6\u69cb\u53ef \u7de8\u88fd\u6210\u591a\u8a9e\u7684\u8a5e\u5f59\u7db2\uf937\uff0c\u6210\u70ba\u591a\u8a9e\u74b0\u5883\u4e2d\u6240\u9700\u4e4b\u8a9e\u8a00\u77e5\uf9fc\u7d50\u69cb\u7684\u57fa\u790e\u8cc7\uf9be\u3002 \u5716\u4e8c\u3001 SINICA BOW \u67b6\u69cb\u5716 \u4e09\u3001\u77e5\u8b58\u672c\u9ad4\u5c0d\u61c9\u8207\u69cb\u8a5e\u5206\u6790 (\u4e00) \u7814\u7a76\u8cc7\u6599 \u5c0d\u9019\u4e9b\u8a5e\u5178\u4e2d\u672a\u6536\u9304\u7684\u6a19\u984c\u8a5e\u800c\u8a00\uff0c\u7531\u65bc\u7f3a\u4e4f\u8db3\u5920\u4e4b\u4e0a\u4e0b\u6587\u8cc7\u8a0a\uff0c\u4e0d\u6613\u4ee5\u8a08\u7b97\u8a5e\u5f59 \u5171\u73fe\u5ea6\u7684\u65b9\u5f0f\u4f86\u9032\u884c\u8a5e\u5f59\u64f4\u5c55\u3002\u56e0\u6b64\uff0c\u672c\u7814\u7a76\u5728\u8a5e\u5f59\u5c64\u6b21\u4e0a\u5c0d\u9019\u4e9b\u672a\u77e5\u8a5e\u9032\u884c\u5206\u6790\u8207\u8655 \u7406\u3002\u5176\u4e2d\uff0c\u4ee5\u8a5e\u5f59\u6240\u5305\u542b\u7684\u8a5e\u7fa9\u6982\u5ff5\u9032\u884c\u6982\u5ff5\u64f4\u5c55\u4ee5\u627e\u51fa\u69cb\u6210\u8a5e\u5f59\u7684\u6982\u5ff5\u5728\u77e5\u8b58\u672c\u9ad4\u4e0a \u7684\u4f4d\u7f6e\u4e26\u5ef6\u4f38\u662f\u672c\u6587\u7814\u7a76\u7684\u4e3b\u8981\u65b9\u5411\u3002\u4ee5\u6a19\u984c\u8a5e\u6240\u5305\u542b\u7684\u6982\u5ff5\u4f5c\u70ba\u57fa\u672c\u55ae\u4f4d\u5247\u53ef\u5c07\u4e4b\u8207 \u5132\u5b58\u77e5\u8b58\u6982\u5ff5\u7684\u77e5\u8b58\u672c\u9ad4\u9032\u884c\u5c0d\u61c9\u9023\u7d50\u3002\u800c\u5728\u9032\u884c\u6982\u5ff5\u5206\u6790\u4e0a\uff0c\u56e0\u8a5e\u5f59\u8207\u6982\u5ff5\u7684\u5c0d\u61c9\u904e \u7a0b\u53ef\u80fd\u7522\u751f\u6b67\u7fa9\uff0c\u6240\u4ee5\u9700\u8981\u7d0d\u5165\u8655\u7406\u6b67\u7fa9\u7684\u6a5f\u5236\u3002 \u6a19\u984c\u8a5e Ki \u6210\u5206\u8a5e Ki2 \u6210\u5206\u8a5e Kij \u6210\u5206\u8a5e Ki1 \u4e2d\u6587\u8a5e\u5f59\u7db2\u8def \u4e2d\u82f1\u96d9\u8a9e\u77e5\u8b58\u672c\u9ad4 \u2026 3. \u52d5\u8a5e + \u5c08\u6709\u540d\u8a5e(\u4eba\u540d) \u4f8b\uff1a \u56de\u5473\uff0f\u8521\u60e0\u98a8 \u627e\u56de\uff0f\u592a\u9b6f\u95a3 \u4e8c\u3001\u5be6\u9ad4\u9a45\u52d5 entirety driven\uff1a\u7121\u52d5\u8a5e\u7684 \u56db\u3001\u6982\u5ff5\u64f4\u5c55\u8207\u7fa4\u96c6\u7e2e\u6e1b (\u4e00) \u6982\u5ff5\u64f4\u5c55\u8207\u7fa4\u96c6 \u5728\u900f\u904e\u6210\u5206\u8a5e\u5c07\u6a19\u984c\u8a5e\u5c0d\u61c9\u81f3 BOW \u6982\u5ff5\u4e4b\u5f8c\uff0c\u4fbf\u53ef\u4ee5\u64f4\u5c55\u5f97\u5230\u4e00\u7d44\u6a19\u984c\u8a5e\u53ca\u5176\u6210 \u5206\u6982\u5ff5\uff0c\u4ee5\u53ca\u6210\u5206\u6982\u5ff5\u9023\u7d50\u5230 SUMO \u4e0a\u7684\u6982\u5ff5\u7bc0\u9ede\u96c6\u5408\u3002\u800c\u56e0\u77e5\u8b58\u672c\u9ad4\u672c\u8eab\u6240\u5177\u5099\u7684 \u7d50\u69cb\u7cfb\u7d71\uff0c\u6240\u4ee5\u53ef\u4f7f\u7528\u7bc0\u9ede\u9593\u7684\u6982\u5ff5\u8ddd\u96e2\u5b9a\u7fa9\u51fa\u76f8\u4f3c\u6982\u5ff5\uff0c\u9032\u800c\u8a08\u7b97\u76f8\u4f3c\u7fa4\u96c6\uff0c\u4f7f\u5f97\u6210 \u5206\u8a5e\u5f97\u4ee5\u64f4\u5c55\u5c0d\u61c9\u81f3\u77e5\u8b58\u672c\u9ad4\u4e0a\u4e26\u900f\u904e\u7fa4\u96c6\u7684\u65b9\u5f0f\u5f62\u6210\u7fa4\u5167\u5dee\u7570\u5c0f\uff0c\u7fa4\u9593\u5dee\u7570\u5927\u7684\u6982\u5ff5 BOW \u64f4\u5c55\u7d50\u679c WN ID SUMO node SUMO SUMO \u6982\u5ff5\u7bc0\u9ede\u4f4d\u7f6e \u6982\u5ff5\u7fa4\u96c6 \u4e2d\u8b6f unit of \u6e2c\u91cf\u55ae C1 C2 C3 C4 \u4e94\u3001\u7d50\u8ad6 1.2.3.11.50.,unit of measure,\u91cf\u5ea6\u55ae \u746a\u7459\u7dda 09870127N measure \u4f4d \u4f4d,C,_unit_of_measure cluster 4 \u746a\u7459\u7dda 09870127N constant quantity \u5e38\u91cf 1.2.3.11.48.,constant quantity,\u5e38 \u91cf,C,_constant_quantity \u8edf\u9ad4 \u52d5\u7269 \u8edf\u9ad4 \u52d5\u7269 \u4eba \u9020 \u7269 1 1 \u7269 \u672c\u7814\u7a76\u4e3b\u8981\u76ee\u7684\u5728\u65bc\u63a2\u8a0e\u4ee5\u6982\u5ff5\u64f4\u5c55\u7684\u65b9\u5f0f\u5c07\u539f\u5148\u5177\u6709\u9818\u57df\u7279\u6b8a\u6027\u7684\u6578\u4f4d\u535a\u7269\u9928 \u7406 \u91cf 3 \u5178\u85cf\u54c1\u6a19\u984c\u9032\u884c\u6210\u5206\u6982\u5ff5\u5206\u6790\uff0c\u4e26\u5c0d\u61c9\u81f3\u77e5\u8b58\u672c\u9ad4\u4e0a\u7684\u7bc0\u9ede\u3002\u518d\u4ee5\u69cb\u8a5e\u6a23\u5f0f\u5c07\u6982\u5ff5\u7fa4\u96c6 cluster 4 \u746a\u7459 10543998N mineral \u7926\u7269 1.1.1.1.1.2.4.,mineral,\u7926 \u7269,C,_mineral \u85dd \u8853 \u54c1 \u88dd\u7f6e 1 2 \u91cf\u5ea6 \u5e38\u91cf \u55ae\u4f4d 1 \u9032\u884c\u7e2e\u6e1b\uff0c\u5f97\u5230\u95dc\u806f\u6982\u5ff5\u7fa4\u96c6\u3002\u5efa\u69cb\u7fa4\u96c6\u4e26\u4ee5\u69cb\u8a5e\u6a23\u5f0f\u7be9\u9078\u95dc\u806f\u7fa4\u96c6\u7684\u4e00\u500b\u597d\u8655\u662f\u7fa4\u96c6 1 cluster 5 \u9593\u7121\u4e92\u65a5\u6027\uff0c\u53ef\u907f\u514d\u7af6\u722d\u800c\u72a7\u7272\u6709\u4ee3\u8868\u6027\u7684\u7fa4\u96c6\u3002\u7d50\u679c\u5c07\u4f7f\u4e0d\u540c\u9818\u57df\u4e4b\u5178\u85cf\u54c1\u80fd\u85c9\u7531\u6a19 (\u4e8c) \u77e5\u8b58\u672c\u9ad4\u5c0d\u61c9\u7b56\u7565 \u73fe\u6709\u5df2\u958b\u767c\u4e4b\u77e5\u8b58\u672c\u9ad4\u53ef\u4ee5\u7528\u4f86\u4f5c\u70ba\u77e5\u8b58\u4ea4\u63db\u8207\u77e5\u8b58\u5132\u5b58\u4e4b\u57fa\u790e\uff0c\u5982 SUMO \u8207 MILO(Mid-Level Ontology) \u3002\u4f46\u4e00\u822c\u6578\u4f4d\u535a\u7269\u9928\u5178\u85cf\u9805\u76ee\u5747\u5177\u6709\u5176\u7279\u6b8a\u6027\uff0c\u56e0\u6b64\u7121\u6cd5 \u9806\u5229\u5728\u6cdb\u7528\u7684\u77e5\u8b58\u672c\u9ad4\u4e0a\u627e\u5230\u5c0d\u61c9\u7bc0\u9ede\uff0c\u4f8b\u5982\u6578\u4f4d\u5178\u85cf\u570b\u5bb6\u578b\u8a08\u756b\u4e2d\u4fbf\u6709\u8d85\u904e 96%\u7684\u9805 \u76ee\u7121\u6cd5\u5728 SUMO \u4e2d\u76f4\u63a5\u627e\u5230\u5c0d\u61c9\u7bc0\u9ede\u3002 \u7531\u65bc\u7d55\u5927\u90e8\u5206\u5178\u85cf\u54c1\u6a19\u984c\u7121\u6cd5\u76f4\u63a5\u5c0d\u61c9\u81f3\u8a5e\u5178\u7d00\u9304\uff0c\u56e0\u6b64\u5728\u5efa\u69cb\u6574\u500b\u5178\u85cf\u5167\u5bb9\u7684\u77e5 \u8b58\u7cfb\u7d71\u6642\uff0c\u53ef\u4ee5\u9078\u64c7\u7684\u65b9\u5411\u4e3b\u8981\u6709\u4e8c\uff1a (1)\u81ea\u884c\u5efa\u7acb\u9818\u57df\u7279\u7528\u4e4b\u77e5\u8b58\u672c\u9ad4\u6216(2)\u900f\u904e \u5c0d\u61c9\u7b56\u7565\u5c07\u5178\u85cf\u54c1\u9805\u4e4b\u6a19\u984c\u5c0d\u61c9\u81f3\u73fe\u6709\u77e5\u8b58\u672c\u9ad4\u7bc0\u9ede\u4e0a\u3002 \u4f9d\u64da\u7814\u7a76\u76ee\u7684\uff0c\u672c\u7814\u7a76\u63d0\u51fa\u4e00\u5c0d\u61c9\u7b56\u7565\uff0c\u900f\u904e\u4e2d\u6587\u69cb\u8a5e\u5206\u6790\uff0c\u5148\u5c07\u7121\u6cd5\u76f4\u63a5\u5c0d\u61c9\u4e4b \u6a19\u984c\u8a5e\u5207\u5206\u70ba\u8f03\u5c0f\u7684\u6210\u5206\u8a5e\uff0c\u518d\u4ee5\u8a5e\u5f62\u6bd4\u5c0d\u7684\u65b9\u5f0f\u5c07\u6210\u5206\u8a5e\u8207\u4e2d\u6587\u8a5e\u5f59\u7db2\u8def\u53ca\u4e2d\u82f1\u96d9\u8a9e \u77e5\u8b58\u672c\u9ad4\u4e2d\u73fe\u6709\u7bc0\u9ede\u7522\u751f\u6bd4\u5c0d\u9023\u7d50\uff0c\u5f97\u5230\u4e00\u500b\u5c0d\u61c9\u7d50\u679c\u3002\u85c9\u6b64\u65b9\u5f0f\u53ef\u65bc\u4e0d\u82b1\u8cbb\u9ad8\u984d\u6210\u672c \u7684\u60c5\u6cc1\u4e0b\uff0c\u5728\u6982\u5ff5\u9023\u7d50\u5c64\u6b21\u5c07\u6a19\u984c\u8a5e\u5f59\u64f4\u5c55\u4e26\u5c0d\u61c9\u81f3\u77e5\u8b58\u672c\u9ad4\u4e2d\u3002\u8a73\u7d30\u6b65\u9a5f\u5982\u5716\u4e09\u6240\u793a\u3002 \u5728\u6210\u5206\u8a5e\u7684\u5b9a\u7fa9\u4e0a\uff0c\u672c\u7814\u7a76\u5c07 N \u5b57\u6a19\u984c\u8a5e\u5207\u5206\u6210\u4e8c\u5b57\u6210\u5206\u3001\u4e09\u5b57\u6210\u5206\u3001\u2026\u3001(N-1) \u5b57\u6210\u5206\uff0c\u5c07\u6240\u6709\u7684\u53ef\u80fd\u6210\u5206\u5b9a\u7fa9\u70ba\u6210\u5206\u8a5e\u96c6\u5408\uff0c\u518d\u900f\u904e\u9019\u4e9b\u6210\u5206\u8a5e\u8207 149,751 \u7b46 BOW \u6982\u5ff5\u9032\u884c\u8a5e\u5f62\u6bd4\u5c0d\u8207\u9023\u7d50\u3002 \u5716\u4e09\u3001\u77e5\u8b58\u6982\u5ff5\u64f4\u5c55\u6d41\u7a0b (\u4e09) \u69cb\u8a5e\u5206\u6790 \u5c07\u6a19\u984c\u8a5e\u5207\u5206\u70ba\u6210\u5206\u8a5e\u7684\u5c0d\u61c9\u65b9\u5f0f\u5177\u6709\u589e\u52a0\u5c0d\u61c9\u7d50\u679c\u6578\u91cf\u4e4b\u6548\u679c\uff0c\u7136\u800c\u4ea6\u6709\u7d0d\u5165\u592a \u591a\u6b67\u7fa9\u8cc7\u6599\u7684\u526f\u4f5c\u7528\u3002\u56e0\u6b64\uff0c\u70ba\u4e86\u5728\u77e5\u8b58\u672c\u9ad4\u5c0d\u61c9\u904e\u7a0b\u904e\u6ffe\u904e\u591a\u7684\u975e\u76ee\u6a19\u7d50\u679c\uff0c\u672c\u7814\u7a76 \u900f\u904e CWN \u4e2d\u7684\u8a73\u7d30\u8a5e\u7fa9\u8cc7\u6599\u9032\u884c\u4e2d\u6587\u69cb\u8a5e\u5206\u6790\u89e3\u6c7a\u6b67\u7fa9\u554f\u984c\uff0c\u5c07\u6210\u5206\u8a5e\u69cb\u6210\u6a19\u984c\u8a5e\u7684 \u7d44\u5408\u65b9\u5f0f\u4ee5\u4eba\u5de5\u65b9\u5f0f\u9032\u884c\u8a9e\u8a00\u5206\u6790\uff0c\u6b78\u7d0d\u51fa\u5169\u7a2e\u4e3b\u8981\u7684\u6a23\u5f0f\uff1a\u4e8b\u4ef6\u9a45\u52d5\u8207\u5be6\u9ad4\u9a45\u52d5\u3002 \u4e00\u3001\u4e8b\u4ef6\u9a45\u52d5 event driven\uff1a(\u5c08\u6709\u540d\u8a5e(\u4eba\u540d) +) \u52d5\u8a5e ( +\u53d7\u8a5e) 1. \u5c08\u6709\u540d\u8a5e(\u4eba\u540d) + \u52d5\u8a5e \u4f8b\uff1a \u89e3\u6b67\u7fa9\u8207\u69cb\u8a5e\u5206\u6790 \u6982\u5ff5\u7fa4\u96c6\u7e2e\u6e1b \u6982\u5ff5\u64f4\u5c55\u8207\u5c0d\u61c9\u7d50\u679c \u6982\u5ff5\u64f4\u5c55\u8207\u7fa4\u96c6 1. \u4fee\u98fe\u8a9e + \u4e2d\u5fc3\u8a9e \u8868\u4e00\u3001\u4fee\u98fe\u8a9e + \u4e2d\u5fc3\u8a9e\u6982\u5ff5\u5206\u6790 \u4fee\u98fe\u8a9e + \u4e2d\u5fc3\u8a9e\u6982\u5ff5\u5206\u6790 \u4f8b \u5c6c\u6027\uff0f\u5c08\u6709\u540d\u8a5e(\u5730\u540d) \uff0f\u4e2d\u5fc3\u8a9e \u5c6c\u6027\uff0f\u5c08\u6709\u540d\u8a5e(\u4eba\u540d) \uff0f\u4e2d\u5fc3\u8a9e \u5782\u82b1\uff0f\u84ec\u840a\uff0f\u845b \u7fa4\u96c6\u3002\u672c\u7814\u7a76\u8a2d\u5b9a\u76f8\u4f3c\u6982\u5ff5\u7bc0\u9ede\u70ba\u5728 SUMO \u67b6\u69cb\u4e2d\u8ddd\u96e2\u5404\u6210\u5206\u6982\u5ff5\u8ddd\u96e2\u70ba 2 \u4ee5\u5167\u7684\u6982 (\u7926)\u82d4\u7d0b\u746a\u7459 10544179N mineral \u7926\u7269 1.1.1.1.1.2.4.,mineral,\u7926 \u7269,C,_mineral C7 C6 C5 \u984c\u7684\u9023\u7d50\u800c\u6574\u5408\u6210\u4e00\u77e5\u8b58\u7cfb\u7d71\u3002\u5728\u7814\u7a76\u4e2d\u4ee5\u4eba\u5de5\u6b78\u7d0d\u65b9\u5f0f\u6574\u7406\u51fa\u69cb\u8a5e\u6a23\u5f0f\u4e26\u63d0\u51fa\u5177\u6709\u4ee3 cluster 5 \u5ff5\u7bc0\u9ede\u3002 \u6bcf\u500b\u7d93\u7531 BOW \u64f4\u5c55\u7684\u77e5\u8b58\u6982\u5ff5\u90fd\u53ef\u4ee5\u5728 SUMO \u4e2d\u627e\u5230\u5c0d\u61c9\u7bc0\u9ede\uff0c\u7531\u65bc SUMO \u7684 \u6a39\u72c0\u7d50\u69cb\uff0c\u9019\u4e9b\u6982\u5ff5\u7bc0\u9ede\u96c6\u5408\u6240\u5f62\u6210\u7684\u5b50\u6a39\u4fbf\u53ef\u8996\u70ba\u4e00\u500b\u7fa4\u96c6\u3002\u8868\u4e8c\u4ee5 \"\u746a\u7459\u96d9\u8033\u676f\" \u4f5c\u70ba\u4f8b\u5b50\uff0c\u8aaa\u660e\u6210\u5206\u8a5e\u7d93\u904e\u5c0d\u61c9\u81f3 BOW \u7684\u6210\u5206\u6982\u5ff5\u64f4\u5c55\u4e4b\u5f8c\uff0c\u85c9\u7531 SUMO \u6982\u5ff5\u7bc0\u9ede \u746a\u7459 10617402N mineral \u7926\u7269 1.1.1.1.1.2.4.,mineral,\u7926 \u7269,C,_mineral cluster 5 \u807d 1 \u8ec0\u9ad4 \u8868\u6027\u7684\u7bc4\u4f8b\u4f5c\u70ba\u8aaa\u660e\uff0c\u53ef\u4f5c\u70ba\u672a\u4f86\u5927\u91cf\u81ea\u52d5\u5316\u8655\u7406\u4e4b\u57fa\u790e\u3002 \u7926\u7269 \u90e8\u4ef6 1 7 \u7531\u672c\u7814\u7a76\u6240\u63d0\u51fa\u4e4b\u6982\u5ff5\u8207\u7814\u7a76\u8a2d\u8a08\u53ef\u91dd\u5c0d\u5132\u5b58\u5927\u91cf\u591a\u9818\u57df\u77e5\u8b58\u7684\u55ae\u4e00\u5178\u85cf\u6a5f\u69cb\u6587 1.1.1.1.1.2.4.,mineral,\u7926 \u7d05\u746a\u7459 10617402N mineral \u7926\u7269 \u7269,C,_mineral cluster 5 \u5668\u5b98 \u5b57\u8cc7\u6599\u9032\u884c\u6982\u5ff5\u64f4\u5c55\uff0c\u5c0d\u65bc\u6578\u4f4d\u535a\u7269\u9928\u76f8\u95dc\u7814\u7a76\u53ef\u6709\u6240\u52a9\u76ca\uff0c\u7279\u5225\u662f\u5728\u6f22\u8a9e\u6578\u4f4d\u535a\u7269\u9928 1 \u9ec3\u6587\uff0f\u737b\u516c\uff0f\u96c6 \u5c08\u6709\u540d\u8a5e(\u5730\u540d)\uff0f\u5c6c\u6027\uff0f\u4e2d\u5fc3\u8a9e \u57ce\u6b66\u7e23\uff0f\u7a05\uff0f\u9280 \u6e58\u6f6d\u7e23\uff0f\u9280\uff0f\u9320 \u5e74\u4ee3\uff0f\u6750\u8cea\uff0f\u4e2d\u5fc3\u8a9e \u5149\u7dd2\u5e74\uff0f\u9280\uff0f\u9320 \u4f4d\u7f6e\u8a08\u7b97\u76f8\u4f3c\u5ea6\u8ddd\u96e2\u6240\u5f97\u5230\u7684\u6982\u5ff5\u7fa4\u96c6\u3002\u7531\u672c\u4f8b\u4e2d\u53ef\u77e5\u746a\u7459\u96d9\u8033\u676f\u7684\u6210\u5206\u8a5e\u5c0d\u61c9\u5230 SUMO \u6642\uff0c\u5171\u53ef\u5728\u77e5\u8b58\u672c\u9ad4\u6a39\u72c0\u7d50\u69cb\u4e2d\u5f62\u6210\u4e03\u500b\u4e3b\u8981\u7fa4\u96c6\u3002 \u8868\u4e8c\u3001\u6982\u5ff5\u7fa4\u96c6\u7bc4\u4f8b\uff1a\u746a\u7459\u96d9\u8033\u676f \u5f69\u7d0b\u746a\u7459 1.1.1.1.1.2.4.,mineral,\u7926 \u7684\u8cc7\u8a0a\u6aa2\u7d22\u61c9\u7528\u4e0a\u3002\u540c\u6642\u4ea6\u53ef\u4f5c\u70ba\u67e5\u8a62\u64f4\u5c55\u76f8\u95dc\u7814\u7a76\u4e4b\u53c3\u8003\u3002\u800c\u7531\u65bc\u5c08\u6709\u540d\u8a5e\u8fa8\u8b58\u53ca\u8655 10740932N mineral \u7926\u7269 \u7269,C,_mineral cluster 5 \u7406\u4e0a\u4e4b\u56f0\u96e3\uff0c\u5f8c\u7e8c\u7814\u7a76\u4e0a\u53ef\u5c0e\u5165\u5408\u9069\u7684\u540d\u7a31\u8fa8\u8b58\u65b9\u6cd5\u4ee5\u4f7f\u8655\u7406\u7bc4\u570d\u80fd\u66f4\u81fb\u5b8c\u6574\u3002 \u5716\u56db\u3001SUMO \u5b50\u6a39\u7fa4\u96c6\u8207\u6b21\u6578\u5206\u5e03(\u4ee5 \"\u746a\u7459\u96d9\u8033\u676f\" \u70ba\u4f8b) 1.1.1.1.1.2.4.,mineral,\u7926 \u7d05\u689d\u7d0b\u746a\u7459 10740932N mineral \u7926\u7269 \u7269,C,_mineral cluster 5 \u6f22 \uff0f\u9752\u7389\uff0f\u74b2 \u5e74\u4ee3\uff0f\u6027\u8cea\uff0f\u4e2d\u5fc3\u8a9e \u5168\u8700\uff0f\u85dd\u6587\uff0f\u5fd7 \u6f22\uff0f\u4eba\u7269\u756b\uff0f\u50cf \u5e74\u4ee3\uff0f\u7d50\u69cb\uff0f\u4e2d\u5fc3\u8a9e \u5168\u5510\uff0f\u8072\u5f8b\uff0f\u8ad6 \u6f22\u9b4f\uff0f\u53e2\u66f8\uff0f\u9078 \u6750\u8cea\uff0f\u529f\u80fd\uff0f\u4e2d\u5fc3\u8a9e \u5149\u7e96\uff0f\u9023\u63a5\uff0f\u5668 \u7db2\u7d50\u8349\uff0f\u96e8\uff0f\u8863 \u6750\u8cea\uff0f\u6a23\u5f0f\uff0f\u4e2d\u5fc3\u8a9e \u746a\u7459\uff0f\u96d9\u8033\uff0f\u676f \u6027\u8cea\uff0f\u4e2d\u5fc3\u8a9e \u58de\u6b7b\u6027\uff0f\u8178\u708e art work \u85dd\u8853\u54c1 \u54c1,C,_art_work cluster 3 \u503c\u5f97\u7559\u610f\u7684\u662f\uff0c\u57fa\u65bc\u7fa4\u96c6\u4e2d\u5305\u542b\u7bc0\u9ede\u7684\u6578\u91cf\u591a\u5be1\uff0c\u6211\u5011\u6307\u5b9a\u7d66\u7fa4\u96c6 5 \u8f03\u9ad8\u7684\u91cd\u8981\u7a0b \u746a\u7459\u7d0b\u642a\u74f7\u5668 02169007N 1.1.1.1.2.5.13.,art work,\u85dd\u8853 (\u4e8c) \u7fa4\u96c6\u7e2e\u6e1b \u5370\u82b1\u7a05\uff0f\u689d\u4f8b \u74f7\u9435\u5668 02169007N art work \u85dd\u8853\u54c1 cluster 3 \u5f59\u3002 \u54c1,C,_art_work \u9ec3\u746a\u7459\uff0f\u7159\uff0f\u58fc \u746a\u7459\u96d9\u8033\u676f BOW \u64f4\u5c55\u7d50\u679c WN ID SUMO node SUMO \u4e2d\u8b6f SUMO \u6982\u5ff5\u7bc0\u9ede\u4f4d\u7f6e \u6982\u5ff5\u7fa4\u96c6 \u746a\u7459\u8c9d 01466296N mollusk \u8edf\u9ad4\u52d5 \u7269 1.1.1.1.2.4.8.14.15.9.,mollusk,\u8edf\u9ad4 \u52d5\u7269,C,_mollusk cluster 1 01466296N mollusk \u7269 cluster 2 \u746a\u7459\u82b1\u7d0b\u7684\u642a 1.1.1.1.2.5.13.,art work,\u85dd\u8853 02509854A hearing \u807d cluster 7 \u689d\u4ef6\u3002\u7d93\u7fa4\u96c6\u7e2e\u6e1b\u5f8c\uff0c\u539f\u59cb\u6a19\u984c\u8a5e\u7684\u76f8\u4f3c\u6982\u5ff5\u5ef6\u4f38\u8a5e\u96c6\u4fbf\u662f\u5169\u500b\u7e2e\u6e1b\u5f8c\u6982\u5ff5\u7fa4\u96c6\u4e2d\u7684\u8a5e \u807d,C,_hearing \u96d9\u8033\u7684 1.1.2.8.38.84.87.92.,hearing, \u56db\u4e2d\u5404 SUMO \u5b50\u6a39\u7bc0\u9ede\u53f3\u5074\u4e4b\u6578\u5b57\u70ba\u6210\u5206\u8a5e\u76f8\u95dc\u6982\u5ff5\u6578\u91cf\uff0c\u4f5c\u70ba\u9078\u53d6\u7fa4\u96c6\u8207\u5426\u7684\u52a0\u6b0a \u7269,C,_mollusk \u746a\u7459\u8c9d \u8edf\u9ad4\u52d5 1.1.1.4.11.25.46.57.,mollusk,\u8edf\u9ad4\u52d5 \u7e8f\u7d72\u746a\u7459 10740932N mineral \u7926\u7269 1.1.1.1.1.2.4.,mineral,\u7926 \u6b64\u65b9\u6cd5\u4e2d\u95dc\u9375\u7684\u5224\u65b7\u57fa\u790e\u70ba\u5404\u7fa4\u96c6\u6240\u9023\u63a5\u7684 SUMO \u6982\u5ff5\u7bc0\u9ede\u8207\u69cb\u8a5e\u6a23\u5f0f\u7684\u642d\u914d\u3002 \u7269,C,_mineral cluster 5 \u96d9\u8033\u7684 00236774A body part \u8ec0\u9ad4\u90e8 \u4ef6 1.1.1.1.2.4.9.18.,body part,\u8ec0\u9ad4\u90e8 \u4ef6,C,_body_part cluster 6 04189008N organ \u5668\u5b98 cluster 6 \u81f3\u4e03\u500b\u7fa4\u96c6\u7684\u6240\u6709\u6982\u5ff5\u7e2e\u6e1b\u6210\u7fa4\u96c6 3\u3001\u7fa4\u96c6 5 \u4ee5\u53ca\u7fa4\u96c6 6 \u7b49\u4e09\u500b\u5177\u6709\u4ee3\u8868\u6027\u7684\u7fa4\u96c6\u3002\u5716 \u5b98,C,_organ \u96d9\u8033\u5fc3 1.1.1.1.2.4.9.18.23.,organ,\u5668 \u7531 \"\u746a\u7459\u96d9\u8033\u676f\" \u4fee\u98fe\u8a9e\u6982\u5ff5\uff0c\u5206\u5225\u70ba\u6750\u8cea\u8207\u6a23\u5f0f\u3002\u56e0\u6b64\u900f\u904e\u69cb\u8a5e\u6a23\u5f0f\u6240\u9032\u884c\u7684\u7fa4\u96c6\u7e2e\u6e1b\u4fbf\u53ef\u5c07\u539f\u672c\u64f4\u5c55 \u53c3\u8003\u6587\u737b</td></tr><tr><td>\u7684, \u4f46\u5728\u8f49\u63db\u4e0a\u53ef\u4ee5\u7528\u4e00\u5c0d\u8a5e\u8207\u8a5e\u4e4b\u9593\uff0c\u591a\u7d44\u6982\u5ff5\u5c0d\u6982\u5ff5\u76f8\u4f3c\u5ea6\u4e2d\u6700\u9ad8\u7684\u90a3\u7d44\u4f86\u4f5c\u70ba\u8a9e \u7fa9\u76f8\u4f3c\u5ea6\u7684\u4ee3\u8868\u3002\u56e0\u6b64\u53ef\u4ee5\u7c21\u55ae\u8f49\u63db\u6210\u8a5e\u8207\u8a5e\u7684\u76f8\u4f3c\u5ea6\u8a08\u7b97\u3002 \u8cc7\u8a0a\u6aa2\u7d22\u4e00\u822c\u53ef\u91dd\u5c0d\u6aa2\u7d22\u7684\u8cc7\u6599\u985e\u578b\u5340\u5206\u70ba\u5169\u7a2e\uff0c\u7b2c\u4e00\u7a2e\u662f\u91dd\u5c0d\u7db2\u969b\u7db2\u8def\u4e0a\u6240\u6709\u7684 \u8cc7\u6599\u5167\u5bb9\u6240\u9032\u884c\u7684\u6aa2\u7d22\uff0c\u7531\u65bc\u6aa2\u7d22\u7684\u7bc4\u570d\u592a\u904e\u5ee3\u6cdb\uff0c\u56e0\u6b64\u5fc5\u9808\u900f\u904e\u8a31\u591a\u4e0d\u540c\u7684\u7b56\u7565\u4f86\u91dd \u5c0d\u67e5\u8a62\u95dc\u9375\u5b57\u9032\u884c\u64f4\u5c55\u4ee5\u6c42\u627e\u51fa\u4f7f\u7528\u8005\u6709\u8208\u8da3\u7684\u5167\u5bb9\uff0c\u5927\u591a\u6578\u7684\u7db2\u969b\u7db2\u8def\u641c\u5c0b\u5f15\u64ce\u7db2\u7ad9 \u4e2d\u82f1\u96d9\u8a9e\u77e5\u8b58\u672c\u9ad4\u8a5e\u7db2(Sinica BOW)[8]\u662f\u4e00\u7d50\u5408\u8a5e\u7db2(WordNet)\u77e5\uf9fc\u672c\u9ad4\u8207\uf9b4 \u57df\u6a19\u8a18\u7684\u8a5e\u5f59\u77e5\uf9fc\u5eab\uff0c\u7531\u4e2d\u592e\u7814\u7a76\u9662\u8a9e\u8a00\u6240\u4e2d\u6587\u8a5e\u5f59\u7db2\u8def\u5c0f\u7d44\u8207\u8cc7\u8a0a\u6240\u4e2d\u6587\u8a5e\u77e5\u8b58\u5eab\u5c0f \u7d44\u5408\u4f5c\u5efa\u7f6e\uff0c\u5f9e\u8a9e\u8a00\u5de5\u7a0b\u7684\u89d2\ufa01\uff0c\u4ee5\u53f0\u7063\u5730\u5340\u7684\u8a9e\u8a00\u4f7f\u7528\u70ba\u7d93\u9a57\u57fa\u790e\uff0c\u63d0\u4f9b\u8a9e\u8a00\u548c\u8a9e\u8a00\u3001 \u8a9e\u8a00\u548c\u6982\uf9a3\u4ee5\u53ca\u8a9e\u8a00\u548c\uf9b4\u57df\u7684\u8cc7\u8a0a\uff0c\u751a\u81f3\u662f\u8de8\u8a9e\u8a00\u9593\u7684\u8a0a\u606f\u3002Sinica BOW\u4ee5\u5efa\uf9f7\u4e00\u5b8c\u6574 \u7cbe\u78ba\u7684\u4e2d\u82f1\u5c0d\u8b6f\u8cc7\uf9be\u5eab\u53ca\u6aa2\uf96a\u4ecb\u9762\u70ba\u76ee\u7684\uff0c\u4f5c\u70ba\uf969\u4f4d\u5178\u85cf\u77e5\uf9fc\u570b\u969b\u5316\u7684\u57fa\u790e\uff1b\u4e26\u6301\u7e8c\u5efa \uf9f7\u5404\uf9b4\u57df\u4e4b\u96d9\u8a9e\uf9b4\u57df\u8fad\u5178\uff0c\u4ee5\u4f5c\u70ba\u5404\uf9b4\u57df\uff0f\u5178\u85cf\u4e4b\u96d9\u8a9e\u63a7\u5236\u8a5e\u5f59\uf96b\u8003\u6a19\u6e96\u3002\u4e2d\u82f1\u96d9\u8a9e\u77e5 \u4e0a\u4f4d(hypernym)\u3001\u9ad4\uf9b5(instantiation)\u9019\u4e09\u7a2e\uf9d0\u5225\u986f\u793a\u540c\u7fa9\u8a5e\u96c6\u548cSUMO\u6982\uf9a3\u9593\u7684\u5c0d \u61c9\u95dc\u4fc2\u3002\u9664\u6b64\uff0c\u66f4\u4ee5\u300c\u4e2d\u570b\u5716\u66f8\u5206\uf9d0\u6cd5\u300d\u70ba\u57fa\u6e96\uff0c\u4e26\uf96b\u8003\u5404\u77e5\uf9fc\u5206\uf9d0\u8207\u5be6\u969b\u7814\u7a76\u7d93\u9a57\uff0c \u63d0\u51fa\uff1a\u5305\u542b\u4e5d\u5927\uf9d0\u7684\u77e5\uf9fc\u5206\uf9d0(Knowledge Content)\uff0c\u6db5\u84cb427\u500b\uf9b4\u57df\u3002\u53e6\u5916\uff0c\u4e26\u56e0\u61c9 \u8a9e\u8a00\u8cc7\u6e90\u7279\u6027\u52a0\u5165\u4e0b\uf99c\u8a9e\u8a00\u4f7f\u7528(Language Usage)\u7684\u5404\uf9d0\u8a0a\u606f\uff1a\u5c08\u540d(\uf96f\u660e\u6587\u5b57\u7b26\u865f \u7684\u6307\u6d89)(Proper Name)\u3001\u8a9e\u9ad4(\uf96f\u660e\u6587\u5b57\u7b26\u865f\u7684\u4f7f\u7528)(Genre/Strata)\u3001\u5404\u7a2e\u8a9e\u8a00 \uff0f\u8a5e\u6e90(Language/Etymology)\u3001\u5404\u570b\u5730\u540d(Country Name)\u3002\uf9b4\u57df\u968e\u5c64\u7684\u5efa\uf9f7\u5728\u65bc\u66ff \u5c0d\u65bc\u5132\u5b58\u591a\u6a23\u9818\u57df\u77e5\u8b58\u7684\u6578\u4f4d\u535a\u7269\u9928\u800c\u8a00\uff0c\u5c07\u5178\u85cf\u54c1\u9805\u6db5\u84cb\u7684\u77e5\u8b58\u6982\u5ff5\u5c0d\u61c9\u81f3\u77e5\u8b58 \u7d50\u69cb\u53ef\u4f5c\u70ba\u8a31\u591a\u5ef6\u4f38\u61c9\u7528\u8207\u7814\u7a76\u4e4b\u57fa\u790e\uff0c\u4f8b\u5982\u67e5\u8a62\u64f4\u5c55\u8207\u8de8\u8a9e\u8a00\u77e5\u8b58\u4ea4\u63db\u3002\u800c\u5178\u85cf\u54c1\u9805 \u4e4b\u6a19\u984c\u540d\u7a31\u53ef\u7528\u4f86\u4f5c\u70ba\u5178\u85cf\u54c1\u7279\u6027\u7684\u5177\u9ad4\u63cf\u8ff0\u3002\u672c\u7814\u7a76\u63a1\u7528\u4e2d\u592e\u7814\u7a76\u9662\u4e2d\u6587\u8a5e\u77e5\u8b58\u5eab\u5c0f \u7d44\u6240\u958b\u767c\u7684\u65b7\u8a5e\u7cfb\u7d71\u5c0d\u6578\u4f4d\u5178\u85cf\u570b\u5bb6\u578b\u8a08\u756b\u4e2d\u7684\u5178\u85cf\u54c1\u6a19\u984c\u9032\u884c\u65b7\u8a5e[12][13]\uff0c\u53d6\u5176\u4e2d \u4e8c\u81f3\u4e94\u5b57\u8a5e\u6240\u69cb\u6210\u7684\u5178\u85cf\u54c1\u6a19\u984c\u4f5c\u70ba\u7814\u7a76\u8cc7\u6599\uff0c\u5171 39,765 \u7b46\u3002\u9019\u4e9b\u6a19\u984c\u5206\u5c6c\u65bc\u751f\u7269\u3001 \u8003\u53e4\u3001\u5730\u8cea\u3001\u4eba\u985e\u5b78\u3001\u6a94\u6848\u3001\u62d3\u7247\u3001\u5668\u7269\u3001\u66f8\u756b\u3001\u5730\u5716\u8207\u9059\u6e2c\u3001\u5584\u672c\u53e4\u7c4d\u3001\u65b0\u805e\u3001\u6f22\u7c4d \u7f85\u6f22\u677e\uff0f\u54ed\u4e86 \u5c0f\u5b78\u751f\uff0f\u8df3\u821e 2. \u5c08\u6709\u540d\u8a5e(\u4eba\u540d) + \u52d5\u8a5e +\u53d7\u8a5e \u4f8b\uff1a \u56dd\u4ed4\uff0f\u9a0e\uff0f\u6728\u99ac 1.1.1.1.2.5.,artifact,\u4eba\u9020 \u7531\u65bc\u6982\u5ff5\u64f4\u5c55\u5f8c\u6240\u5f97\u5230\u7684\u7fa4\u96c6\u5f80\u5f80\u5305\u542b\u592a\u904e\u9f90\u96dc\u7684\u5167\u5bb9\uff0c\u56e0\u6b64\u6709\u5fc5\u8981\u5efa\u7acb\u4e00\u500b\u7fa4\u96c6 \u5ea6\uff0c\u9019\u662f\u4ee5\u8a5e\u5178\u89c0\u5ff5\u4f86\u9032\u884c\u7684\u8a2d\u5b9a\uff0c\u56e0\u70ba\u8a5e\u5178\u4e2d\u5305\u542b\u8f03\u591a\u7684\u9805\u76ee\u81ea\u7136\u662f\u6982\u5ff5\u4e0a\u91cd\u8981\u7684\u7fa4 \u96d9\u8033\u74f6 02185088N artifact \u4eba\u9020\u7269 \u7269,C,_artifact cluster 3 \u7e2e\u6e1b\u7684\u6a5f\u5236\u4ee5\u6ffe\u53bb\u8207\u539f\u59cb\u6a19\u984c\u5dee\u7570\u8f03\u5927\u7684\u6982\u5ff5\u7fa4\u96c6\uff0c\u50c5\u4fdd\u7559\u4e3b\u8981\u76f8\u95dc\u7684\u6982\u5ff5\u7fa4\u96c6\u3002\u6b64 \u96c6\u9805\u76ee\u3002\u800c\u4fee\u98fe\u8a9e\u7684\u985e\u5225\u7d93\u672c\u6587\u5206\u6790\u53ef\u5f97\u5230\u6709\u5c6c\u6027\u3001\u5c08\u6709\u540d\u8a5e\u3001\u5e74\u4ee3\u3001\u6750\u8cea\u3001\u6027\u8cea\u3001\u7d50 2. \u4e2d\u5fc3\u8a9e(+\u9023\u63a5\u8a5e\u6216\u4ecb\u7cfb\u8a5e) \u4e2d\u5fc3\u8a9e \u4f8b\uff1a \u56de\u9867\uff0f\u8207\uff0f\u5c55\u671b artifact \u4eba\u9020\u7269 \u7269,C,_artifact cluster 3 \u61c9\u6b63\u78ba\u77e5\u8b58\u672c\u9ad4\u5206\u652f\u4e4b\u7fa4\u96c6\uff0c\u800c\u62cb\u68c4\u5176\u9918\u7fa4\u96c6\u4e0d\u7b26\u5408\u69cb\u8a5e\u539f\u5247\u4e4b\u7fa4\u96c6\u3002 \u96d9\u8033\u5e73\u5e95\u9152\u676f 03291208N 1.1.1.1.2.5.,artifact,\u4eba\u9020 \u76f8\u5c0d\u61c9\u5206\u652f\u4e2d\u904e\u6ffe\u51fa\u5177\u6709\u9ad8\u76f8\u95dc\u6027\u4e4b\u5c0d\u61c9\u7fa4\u96c6\uff0c\u7531\u5df2\u64f4\u5c55\u4e26\u5206\u7fa4\u5f8c\u7684\u6982\u5ff5\u7fa4\u96c6\u4e2d\u4fdd\u7559\u5c0d \u9748\u829d\uff0f\u548c\uff0f\u725b\u6a1f 02185088N artifact \u4eba\u9020\u7269 \u7269,C,_artifact cluster 3 \u4ee5\u69cb\u8a5e\u539f\u5247\u5340\u8fa8\u51fa\u6b64\u6a19\u984c\u8a5e\u4e2d\u4e3b\u8981\u7684\u4e2d\u5fc3\u8a9e\u4ee5\u53ca\u4fee\u98fe\u8a9e\uff0c\u518d\u4ee5\u6b64\u69cb\u8a5e\u6a23\u5f0f\u81f3\u77e5\u8b58\u672c\u9ad4\u4e2d \u96d9\u8033\u9ecf\u571f\u7a84\u74f6 1.1.1.1.2.5.,artifact,\u4eba\u9020 \u6642\uff0c\u524d\u8ff0\u7531\u4eba\u5de5\u6b78\u7d0d\u4e4b\u69cb\u8a5e\u6a23\u5f0f\u5373\u53ef\u626e\u6f14\u904e\u6ffe\u5668\u4e4b\u89d2\u8272\u3002\u4ee5\u746a\u7459\u96d9\u8033\u676f\u4e00\u4f8b\uff0c\u672c\u7814\u7a76\u5373 \u69cb\u3001\u529f\u80fd\u3001\u6a23\u5f0f\u3001\u6027\u8cea\u7b49\u4e5d\u5927\u985e\u3002</td></tr><tr><td>\u6240\u63d0\u4f9b\u4e4b\u670d\u52d9\u7686\u5c6c\u65bc\u6b64\u985e\u3002\u7b2c\u4e8c\u7a2e\u5247\u662f\u91dd\u5c0d\u7279\u5b9a\u7bc4\u570d\u8cc7\u6599\u6240\u9032\u884c\u7684\u8cc7\u8a0a\u6aa2\u7d22\uff0c\u6b64\u985e\u8cc7\u8a0a \u6aa2\u7d22\u7684\u4f7f\u7528\u8005\u662f\u5728\u8cc7\u6599\u5167\u5bb9\u56fa\u5b9a\u7684\u60c5\u6cc1\u4e0b\u9032\u884c\u67e5\u8a62\uff0c\u4f8b\u5982\u65b0\u805e\u5a92\u9ad4\u7db2\u7ad9\u6216\u662f\u6578\u4f4d\u535a\u7269\u9928 \u751f\u7684\uf9fc\u5225\u78bc\u4f5c\u70ba\u5a92\u4ecb\uff0c\u9032\ufa08\uf905\uf99a\uff0c\u5c07\u6bcf\u500b\u8cc7\u6e90\u4ee5\u53ca\u5404\uf9d0\u8a0a\u606f\uf99a\u7d50\u3002 \u7db2\u7ad9\u3002 \u8b58\u672c\u9ad4\u8a5e\u7db2\u540c\u6642\u63d0\u4f9b\u5177\uf9b4\u57df\u5224\u65b7\u80fd\uf98a\u4e4b\u8cc7\u8a0a\u6aa2\uf96a\u61c9\u7528\u3002\u6b64\u5916\uff0c\u5efa\uf9f7\u9644\u52a0\uf9b4\u57df\u6a19\u8a18\u4e4b\u96d9\u8a9e \u8fad\u5178\u53ca\u6aa2\uf96a\u4ecb\u9762\u4f7f\u4e2d\u82f1\u96d9\u8a9e\u77e5\u8b58\u672c\u9ad4\u8a5e\u7db2\u6210\u70ba\u4e00\u77e5\uf9fc\u52a0\u503c\u96d9\u8a9e\u96fb\u5b50\u8fad\u5178\u3002 \uf967\u540c\u8a5e\u7fa9\u4e2d\u7684\u8a5e\u5f59\u9805\u76ee\u5340\u5225\u5176\u4f7f\u7528\u7684\uf9b4\u57df\u3002\u52a0\u8a3b\uf9b4\u57df\u4fe1\u606f\u53ef\ufa09\u4f4e\u8a5e\u5f59\u6b67\uf962\u6027\uff0c\u589e\u52a0\u8cc7\uf9be \u4ea4\u63db\u6642\u7684\u4e92\u901a\u6027\uff0c\u8f14\u52a9\uf9b4\u57df\u8a5e\u5f59\u5eab\u4e4b\u5efa\u69cb\u3002Sinica BOW\u900f\u904eWordNet1.6 offset\u5ef6\u4f38\u6240\u7522 \u5168\u6587\u3001\u5f71\u97f3\u3001\u5efa\u7bc9\u7b49\u5341\u56db\u500b\u4e3b\u984c\u9818\u57df\uff0c\u5176\u4e2d 96%\u7684\u6a19\u984c\u8a5e\u70ba\u8a5e\u5178\u4e2d\u672a\u6536\u9304\u4e4b\u9805\u76ee\uff0c\u5982\u99ac \u9280\u82b1\u3001\u5609\u7fa9\u4e2d\u5b78\u8207\u746a\u7459\u96d9\u8033\u676f\u7b49\u3002 \u6211\uff0f\u656c\u611b\uff0f\u570b\u7236 1.1.1.1.2.5.16.,device,\u88dd \u96d9\u8033\u5f0f\u8033\u6a5f 02809404N device \u88dd\u7f6e \u7f6e,C,_device cluster 3</td></tr></table>", | |
| "html": null, | |
| "type_str": "table", | |
| "text": "\u500b\u5178\u85cf\u54c1\u6a19\u984c(2~5 \u5b57\u8a5e)\u70ba\u5be6\u9a57\u8cc7\u6599\uff0c\u900f\u904e \u4e2d\u6587\u8a5e\u5f59\u7db2\u8def(Chinese Wordnet; CWN)\u53ca\u4e2d\u82f1\u96d9\u8a9e\u77e5\u8b58\u672c\u9ad4\u8a5e\u7db2(Sinica BOW)\u6240\u5efa Sinica BOW \u4e3b\u8981\u4f7f\u7528\u7684\u8cc7\u6e90\u5305\u542b WordNet\u3001ECTED(English-Chinese Translation Equivalents Database)\u4ee5\u53ca SUMO(Suggested Upper Merged Ontology\uff0c\u5efa\u8b70\u4e0a\u5c64\u5171\u7528\u77e5 \uf9fc\u672c\u9ad4)\u3002\u5176\u4e2d WordNet[9]\u662f 1985 \uf98e\u666e\uf9f4\u65af\u9813\u5927\u5b78\u8a8d\u77e5\u79d1\u5b78\u5be6\u9a57\u5ba4\u4ee5\u73fe\u4ee3\u5fc3\uf9e4\u8a9e\u8a00\u5b78 \u7bc4\u4f8b\u53ef\u5f97\u77e5\u5728 \"\u4fee\u98fe\u8a9e + \u4e2d\u5fc3\u8a9e\" \u7684\u69cb\u8a5e\u6a23\u5f0f\u4e0b\uff0c\u7fa4\u96c6 3 \u6240\u6307\u6d89\u7684 SUMO \u6982\u5ff5 (\u4eba\u9020\u7269\u3001\u88dd\u7f6e\u3001\u85dd\u8853\u54c1) \u6070\u53ef\u8868\u9054\u4e2d\u5fc3\u8a9e\u7684\u6982\u5ff5\u3002\u800c\u7fa4\u96c6 5 \u6240\u6307\u6d89\u7684 SUMO \u6982\u5ff5(\u7926\u7269) \uff0c\u4ee5\u53ca\u7fa4\u96c6 6 \u6240\u6307\u6d89\u7684 SUMO \u6982\u5ff5(\u8ec0\u9ad4\u90e8\u4ef6\u3001\u5668\u5b98)\u5247\u7528\u4f86\u50b3\u9054\u672c\u4f8b\u7684" | |
| } | |
| } | |
| } | |
| } |