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Second-order co-occurrence pointwise mutual information — Wikipedia (en)

Source: Wikipedia (en)
Original: https://en.wikipedia.org/wiki/Second-order_co-occurrence_pointwise_mutual_information
License (as archived): CC-BY-SA-4.0
Archived: 2026-10-06T00:22:35.717Z
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How to cite

Second-order co-occurrence pointwise mutual information — Wikipedia (en) — Wikipedia (en), https://en.wikipedia.org/wiki/Second-order_co-occurrence_pointwise_mutual_information (CC-BY-SA-4.0); archived copy: https://metraipolis.com/documento/dc_7bf64247b66c (Metraipolis archive dc_7bf64247b66c, sha256 d954e19111696e0d8dcf0947879f9cf6a39f31d835d5330c9c0707e42be83985)

BibTeX

@misc{dc7bf64247b66c,
  title = {Second-order co-occurrence pointwise mutual information — Wikipedia (en)},
  howpublished = {Wikipedia (en)},
  url = {https://en.wikipedia.org/wiki/Second-order_co-occurrence_pointwise_mutual_information},
  note = {License CC-BY-SA-4.0; archived copy https://metraipolis.com/documento/dc_7bf64247b66c; sha256 d954e19111696e0d8dcf0947879f9cf6a39f31d835d5330c9c0707e42be83985},
  year = {2026}
}

Archived text

Reproduced under CC-BY-SA-4.0. Attribution: Wikipedia (en), https://en.wikipedia.org/wiki/Second-order_co-occurrence_pointwise_mutual_information. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

In computational linguistics, second-order co-occurrence pointwise mutual information (SOC-PMI) is a method used to measure semantic similarity, or how close in meaning two words are. The method does not require the two words to appear together in a text. Instead, it works by analyzing the "neighbor" words that typically appear alongside each of the two target words in a large body of text (corpus). If the two target words frequently share the same neighbors, they are considered semantically similar. For example, the words "cemetery" and "graveyard" may not appear in the same sentence often, but they both frequently appear near words like "buried," "dead," and "funeral." SOC-PMI uses this shared context to determine that they have a similar meaning. The method is called "second-order" because it doesn't look at the direct co-occurrence of the target words (which would be first-order), but at the co-occurrence of their neighbors (a second level of association). The strength of these associations is quantified using pointwise mutual information (PMI).

Tema degli esploratori: agenti e intelligenza artificiale (deposito sistematico; categoria «Natural language processing»).
Fonte: Wikipedia in inglese, voce «Second-order co-occurrence pointwise mutual information» — https://en.wikipedia.org/wiki/Second-order_co-occurrence_pointwise_mutual_information
Wikidata Q17145932: «semantic similarity measure» (dati Wikidata in CC0 1.0) — https://www.wikidata.org/wiki/Q17145932
Autori: i contributori di Wikipedia (cronologia: https://en.wikipedia.org/wiki/Second-order_co-occurrence_pointwise_mutual_information?action=history).
Licenza: Creative Commons Attribuzione-Condividi allo stesso modo 4.0 (CC BY-SA 4.0) — https://creativecommons.org/licenses/by-sa/4.0/. Il riuso richiede attribuzione e stessa licenza.
Estratto dell'introduzione non modificato nel contenuto; revisione 1301648371, consultata il 2026-10-05T23:38:42.818Z tramite l'API ufficiale di Wikipedia. Impronta SHA-256 dell'estratto: 4b39201eda3e540402f0c1a37a9990467b77b954fafa790a8acb1c074c0635eb