"You shall know a word by the company it keeps." Distributional Semantics as the basis for self supervised learning as in today's large language models. This is what my colleague @MahsaVafaie and I are going to talk about in this #kg2023 lecture excursion.
OpenHPI video: https://open.hpi.de/courses/knowledgegraphs2023/items/4fwf0437tRYK49o8Xd18Eg
youtube video: https://www.youtube.com/watch?v=EYAY8nmhpdg&list=PLNXdQl4kBgzubTOfY5cbtxZCgg9UTe-uF&index=61
slides: https://zenodo.org/records/10185262
@fiz_karlsruhe @fizise @tabea @sashabruns @enorouzi #semantics #distributionalsemantics #llm #llms #cooccurrence #wittgenstein

Very happy to be in #Montpellier today for a "journée d'étude" on the notion of #tupleization in the context of #cooccurrence, #keyness, #frequency and #dispersion. – The opening speaker is Stefan Th. Gries, and the full programme can be found here: https://corli.huma-num.fr/events/untangling-associations-advances-in-collocation-and-keyword-analysis/

#CorpusLinguistics #CLS

I have a hard time finding a #Python implementation of statistical #cooccurrence/#collocation tests like log-likelihood (as described by Dunning 1993). There’s an #RStats implementation in #PolmineR, but isn’t there any for Python? Any hints appreciated. #CorpusLinguistics #ComputationalLinguistics

Hashtags are an incredibly useful feature for annotating posts and have an active role on microblogging platforms such as Twitter and Mastodon. They are particularly helpful for discovering new people to follow and finding interesting posts.

In a separate post, I used Twitter to build hashtag co-occurrence networks based upon a specific […]

https://jrashford.com/2023/02/14/building-user-hashtag-co-occurrence-network-from-timelines-on-mastodon/