Inductive learning for protocol analysis:
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Buch |
| Sprache: | Japanisch Englisch |
| Veröffentlicht: |
Tokyo, Japan
1988
|
| Schriftenreihe: | Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum
512 |
| Schlagwörter: | |
| Abstract: | Abstract: "This paper describes a learning method for building knowledge bases. There are two types of knowledge acquisition systems which extract knowledge from human experts, interactive and non-interactive. This paper describes a non-interactive knowledge acquisition system which acquires a human expert's knowledge by observation. It learns the human expert's problem solving strategies and makes logical rules from temporal sequential data. The learning method of the knowledge acquisition system is interpretation based learning (IBL), which uses advance knowledge in the learning process. Advance knowledge of IBL consists of domain concepts, concept relations and interpretation knowledge, which translates observed data into internal concepts Although explanation based learning (EBL) also uses advance knowledge, which consists of domain theory and operationality criteria, it learns knowledge using the domain theory, but IBL learns the domain theory itself. IBL is a useful knowledge acquisition method when a domain theory has not been prepared. |
| Umfang: | 8 S. |
Internformat
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| 490 | 1 | |a Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum |v 512 | |
| 520 | 3 | |a Abstract: "This paper describes a learning method for building knowledge bases. There are two types of knowledge acquisition systems which extract knowledge from human experts, interactive and non-interactive. This paper describes a non-interactive knowledge acquisition system which acquires a human expert's knowledge by observation. It learns the human expert's problem solving strategies and makes logical rules from temporal sequential data. The learning method of the knowledge acquisition system is interpretation based learning (IBL), which uses advance knowledge in the learning process. Advance knowledge of IBL consists of domain concepts, concept relations and interpretation knowledge, which translates observed data into internal concepts | |
| 520 | 3 | |a Although explanation based learning (EBL) also uses advance knowledge, which consists of domain theory and operationality criteria, it learns knowledge using the domain theory, but IBL learns the domain theory itself. IBL is a useful knowledge acquisition method when a domain theory has not been prepared. | |
| 650 | 4 | |a Künstliche Intelligenz | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Expert systems (Computer science) | |
| 650 | 4 | |a Machine learning | |
| 830 | 0 | |a Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum |v 512 |w (DE-604)BV010943497 |9 512 | |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-007339346 | |
Datensatz im Suchindex
| DE-BY-TUM_call_number | 0111 2001 B 6122-512 |
|---|---|
| DE-BY-TUM_katkey | 767064 |
| DE-BY-TUM_location | 01 |
| DE-BY-TUM_media_number | 040010303969 |
| _version_ | 1821938207020810241 |
| any_adam_object | |
| author | Taki, Hirokazu |
| author_facet | Taki, Hirokazu |
| author_role | aut |
| author_sort | Taki, Hirokazu |
| author_variant | h t ht |
| building | Verbundindex |
| bvnumber | BV010969545 |
| ctrlnum | (OCoLC)21318954 (DE-599)BVBBV010969545 |
| format | Book |
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| id | DE-604.BV010969545 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T10:04:03Z |
| institution | BVB |
| language | Japanese English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-007339346 |
| oclc_num | 21318954 |
| open_access_boolean | |
| owner | DE-91G DE-BY-TUM |
| owner_facet | DE-91G DE-BY-TUM |
| physical | 8 S. |
| publishDate | 1988 |
| publishDateSearch | 1988 |
| publishDateSort | 1988 |
| record_format | marc |
| series | Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum |
| series2 | Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum |
| spellingShingle | Taki, Hirokazu Inductive learning for protocol analysis Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum Künstliche Intelligenz Artificial intelligence Expert systems (Computer science) Machine learning |
| title | Inductive learning for protocol analysis |
| title_auth | Inductive learning for protocol analysis |
| title_exact_search | Inductive learning for protocol analysis |
| title_full | Inductive learning for protocol analysis by H. Taki |
| title_fullStr | Inductive learning for protocol analysis by H. Taki |
| title_full_unstemmed | Inductive learning for protocol analysis by H. Taki |
| title_short | Inductive learning for protocol analysis |
| title_sort | inductive learning for protocol analysis |
| topic | Künstliche Intelligenz Artificial intelligence Expert systems (Computer science) Machine learning |
| topic_facet | Künstliche Intelligenz Artificial intelligence Expert systems (Computer science) Machine learning |
| volume_link | (DE-604)BV010943497 |
| work_keys_str_mv | AT takihirokazu inductivelearningforprotocolanalysis |
Paper/Kapitel scannen lassen
Teilbibliothek Mathematik & Informatik, Berichte
| Signatur: |
0111 2001 B 6122-512 Lageplan |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |