Umjinjo (umbono ovamile)

Igama elithi Umjinjo liyisicabango esibanzi esihlanganisa inqubo yokujinja, iqoqo lamaqembu angumphumela wokujinjwa, kanye nokujutshwa kwezici zifakwe emaqenjini akhiwe. Ukujinja yisicabango esiyisiseko nesiyingxenye yazo zonke izinhlobo zobuqhebeqhebe. Umjinjo ngokwawo wumkhakha wezemfundo oxubuqeqesho, owakhiwa uqeqesho oluhlanganisa injulalwazi, umchazampilo, ukuhlelwa kolwazi, umchazangqondo, izibalomininingo nomchazazibalo.

Izincasiselo

Ibizo elithi umjinjo lingasebenza kokukodwa noma konke okulandelayo:

inqubo yokujinja (ukubandlula nokwabela izinhlobo zezinto emaqenjini ahlukene)^[1]
iqoqo lamaqembu angumphumela, aziwa ngokuthi izigaba ^[2] (also called a classification system)
ukujutshwa kwezici ezigabeni ezakhiwe

Ukujinja—ngomqondo obanzi onikeziwe—kuyisicabango esiyisiseko futhi kuyingxenye yazo zonke izinhlobo zobuqhebeqhebe.

Imithombo

↑ Nakata, Keiichi; Singh, Amrish (31 October 2007). "Collaborative Classification for Group-Oriented Organization of Search Results". In Goh, Dion Hoe-Lian; Foo, Schubert. Social Information Retrieval Systems. IGI Global research collection. Hershey, Pennsylvania: IGI Global (published 2007). pp. 49–50. ISBN 9781599045450. Archived from the original on 24 October 2023. Kulandwe ngomhlaka 18 March 2021. The two approaches in concept classification also extend to a more top-down or a more bottom-up approach in the process of collaborative classification. This refers to the way the collaborative activity of classification is carried out [...] The bottom-up approach might lead to many inconsistencies or a 'free-rider' problem which would not enable an effective development of the classification. Unknown parameter |url-status= ignored (help)
↑ For example: Conference Proceedings of the Second Annual Artificial Intelligence Research Forum: November 16-18, 1987, NASA Ames Research Center, Palo Alto, California. NASA Ames Research Center. 1987. p. 224. Archived from the original on 24 October 2023. Kulandwe ngomhlaka 18 March 2021. [...] Bayes's theorem, that defines the optimal set of classes (a classification) for a given set of examples. Unknown parameter |url-status= ignored (help)

[1] Nakata, Keiichi; Singh, Amrish (31 October 2007). "Collaborative Classification for Group-Oriented Organization of Search Results". In Goh, Dion Hoe-Lian; Foo, Schubert. Social Information Retrieval Systems. IGI Global research collection. Hershey, Pennsylvania: IGI Global (published 2007). pp. 49–50. ISBN 9781599045450. Archived from the original on 24 October 2023. Kulandwe ngomhlaka 18 March 2021. The two approaches in concept classification also extend to a more top-down or a more bottom-up approach in the process of collaborative classification. This refers to the way the collaborative activity of classification is carried out [...] The bottom-up approach might lead to many inconsistencies or a 'free-rider' problem which would not enable an effective development of the classification. Unknown parameter |url-status= ignored (help)

[2] For example: Conference Proceedings of the Second Annual Artificial Intelligence Research Forum: November 16-18, 1987, NASA Ames Research Center, Palo Alto, California. NASA Ames Research Center. 1987. p. 224. Archived from the original on 24 October 2023. Kulandwe ngomhlaka 18 March 2021. [...] Bayes's theorem, that defines the optimal set of classes (a classification) for a given set of examples. Unknown parameter |url-status= ignored (help)

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