Exploring the use of word embeddings and random walks on Wikipedia for the CogAlex shared task
Code (0)
등록된 구현이 없습니다.
Tasks
Information RetrievalNatural Language InferenceSemantic Textual SimilarityWord EmbeddingsWord Sense DisambiguationSimilar Papers 제목 키워드 기반
Towards Exploiting Implicit Human Feedback for Improving RDF2vec Embeddings
RDF2vec is a technique for creating vector space embeddings from an RDF knowledge graph, i.e., representing each entity in the graph as a vector. It first creates sequences of nodes by performing random walks on the grap…
Walk this Way! Entity Walks and Property Walks for RDF2vec
RDF2vec is a knowledge graph embedding mechanism which first extracts sequences from knowledge graphs by performing random walks, then feeds those into the word embedding algorithm word2vec for computing vector represent…
Graph EmbeddingKnowledge Graph EmbeddingKnowledge GraphsBilingual Embeddings with Random Walks over Multilingual Wordnets
Bilingual word embeddings represent words of two languages in the same space, and allow to transfer knowledge from one language to the other without machine translation. The main approach is to train monolingual embeddin…
Machine TranslationWord EmbeddingsWord SimilarityNode Embedding for Homophilous Graphs with ARGEW: Augmentation of Random walks by Graph Edge Weights
Representing nodes in a network as dense vectors node embeddings is important for understanding a given network and solving many downstream tasks. In particular, for weighted homophilous graphs where similar nodes are co…
Node ClassificationIs Wikipedia succeeding in reducing gender bias? Assessing changes in gender bias in Wikipedia using word embeddings
Large text corpora used for creating word embeddings (vectors which represent word meanings) often contain stereotypical gender biases. As a result, such unwanted biases will typically also be present in word embeddings …
ArticlesWord Embeddings