Using Significant Word Co-occurences for the Lexical Access Problem

反義詞「多」和「少」在數量名結構中的不對稱現象－－以語料庫為本的分析 (The Asymmetric Occurences of \textitDou1 and \textitShao3 in the [Numeral + Measure Word/Classifier + Noun] Construction: A Corpus-based Analysis) [In Chinese]

Clustering Words by Projection Entropy

We apply entropy agglomeration (EA), a recently introduced algorithm, to cluster the words of a literary text. EA is a greedy agglomerative procedure that minimizes projection entropy (PE), a function that can quantify t…

Fast Linear Model for Knowledge Graph Embeddings

This paper shows that a simple baseline based on a Bag-of-Words (BoW) representation learns surprisingly good knowledge graph embeddings. By casting knowledge base completion and question answering as supervised classifi…

Semantic Word Clouds with Background Corpus Normalization and t-distributed Stochastic Neighbor Embedding

Many word clouds provide no semantics to the word placement, but use a random layout optimized solely for aesthetic purposes. We propose a novel approach to model word significance and word affinity within a document, an…

WordNet and beyond: the case of lexical access

For humans the main functions of a dictionary is to store information concerning words and to reveal it when needed. While readers are interested in the meaning of words, writers look for answers concerning usage, spelli…