#distributionalsemantics — Public Fediverse posts

In 2013, Mikolov et al. (from Google) published word2vec, a neural network based framework to learn distributed representations of words as dense vectors in continuous space, aka word embeddings.

T. Mikolov et al. (2013). Efficient Estimation of Word Representations in Vector Space. arXiv:1301.3781
https://arxiv.org/abs/1301.3781

#HistoryOfAI #AI #ise2024 #lecture #distributionalsemantics #wordembeddings #embeddings @sourisnumerique @enorouzi @fizise

In lecture 05 of our #ise2024 lecture series, we are introducing the concept of distributed semantics and are referring (amongst others) to Ludwig Wittgenstein and his approach to the philosophy of language, and combine it with the idea of word vectors and embeddings.

lecture slides: https://drive.google.com/file/d/1WcVlkcUr33u5JmFcadkwtePpXJrv03n2/view?usp=sharing

#wittgenstein #nlp #wordembeddings #distributionalsemantics #lecture @fiz_karlsruhe @fizise @enorouzi @shufan @sourisnumerique #aiart #generativeai

Getting ready to leave for #iclc16 in Düsseldorf, here a small teaser for my talk on Tuesday 14:45 on the #affix rivalry between -ity and -ness in #English:
Why to some adjectives take -ity (insular -> insularity), while others take -ness (red -> redness)? Many factors have been considered, I use #distributionalSemantics to explore the role of the adjective's meaning. Mapping the vectors on a two dimensional space with t-SNE, a dimensionality reduction technique, the resulting visualization shows that adjective meaning might indeed be a highly relevant factor. For example, even for adjectives with the same ending -ive, the bases of those taking -ity (e.g. narrativity) and those taking -ness (distinctiveness) fall into two clear clusters.
Looking forward to seeing some of you there :)
#wordformation

Today's #ise2023 lecture was focusing on Naive Bayes Classification, POS Tagging, and distributional semantics with Word Embeddings

https://drive.google.com/drive/folders/11Z3_UGQjGONyHyZbj_kIdgT-LglZH4Ob

#nlp #lecture #classification #wordembeddings #languagemodels #word2vec #hiddenMarkovModel #distributionalsemantics @fizise @KIT_Karlsruhe #stablediffusionart #creativeAI