The proceedings contain 14 papers. The topics discussed include: a survey of embedding models of entities and relationships for knowledge graph completion;graph-based aspect representation learning for entity resoluti...
ISBN:
(纸本)9781952148422
The proceedings contain 14 papers. The topics discussed include: a survey of embedding models of entities and relationships for knowledge graph completion;graph-based aspect representation learning for entity resolution;merge and recognize: a geometry and 2D context aware graph model for named entity recognition from visual documents;joint learning of the graph and the data representation for graph-based semi-supervised learning;contextual BERT: conditioning the language model using a global state;semi-supervised word sense disambiguation using example similarity graph;incorporating temporal information in entailment graph mining;relation specific transformations for open world knowledge graph completion;and PGL at Textgraphs 2020 Shared Task: explanation regeneration using language and graph learning methods.
The proceedings contain 6 papers. The topics discussed include: embedding senses for efficient graph-based word sense disambiguation;context tailoring for text normalization;cross-lingual question answering using comm...
ISBN:
(纸本)9781941643884
The proceedings contain 6 papers. The topics discussed include: embedding senses for efficient graph-based word sense disambiguation;context tailoring for text normalization;cross-lingual question answering using common semantic space;network motifs may improve quality assessment of text documents;better together: combining language and social interactions into a shared representation;and visualization of dynamic reference graphs.
The proceedings contain 12 papers. The topics discussed include: network analysis reveals structure indicative of syntax in the corpus of undeciphered Indus civilization inscriptions;bipartite spectral graph partition...
ISBN:
(纸本)193243254X
The proceedings contain 12 papers. The topics discussed include: network analysis reveals structure indicative of syntax in the corpus of undeciphered Indus civilization inscriptions;bipartite spectral graph partitioning to co-cluster varieties and sound correspondences in dialectology;WikiWalk: random walks on Wikipedia for semantic relatedness;classifying Japanese polysemous verbs based on Fuzzy C-means clustering;measuring semantic relatedness with vector space models and random walks;ranking and semi-supervised classification on large scale graphs using Map-Reduce;opinion graphs for polarity and discourse classification;a cohesion graphbased approach for unsupervised recognition of literal and non-literal use of multiword expressions;social (distributed) language modeling, clustering and dialectometry;and quantitative analysis of treebanks using frequent subtree mining methods.
The proceedings contain 10 papers. The topics discussed include: adapting predominant and novel sense discovery algorithms for identifying corpus-specific sense differences;merging knowledge bases in different languag...
ISBN:
(纸本)9781945626609
The proceedings contain 10 papers. The topics discussed include: adapting predominant and novel sense discovery algorithms for identifying corpus-specific sense differences;merging knowledge bases in different languages;parameter free hierarchical graph-based clustering for analyzing continuous word embeddings;spectral graph-based method of multimodal word embedding;extract with order for coherent multi-document summarization;work hard, play hard: email classification on the avocado and Enron corpora;a graphbased semi-supervised approach for analysis of derivational nouns in Sanskrit;and evaluating text coherence based on semantic similarity graph.
The proceedings contain 9 papers. The topics discussed include: a combination of topic models with max-margin learning for relation detection;nonparametric Bayesian word sense induction;invariants and variability of s...
ISBN:
(纸本)9781937284008
The proceedings contain 9 papers. The topics discussed include: a combination of topic models with max-margin learning for relation detection;nonparametric Bayesian word sense induction;invariants and variability of synonymy networks: self mediated agreement by confluence;word sense induction by community detection;using a Wikipedia-based semantic relatedness measure for document clustering;GrawlTCQ: terminology and corpora building by ranking simultaneously terms, queries and documents using graph random walks;simultaneous similarity learning and feature-weight learning for document clustering;unrestricted quantifier scope disambiguation;and from ranked words to dependency trees: two-stage unsupervised non-projective dependency parsing.
The proceedings contain 8 papers. The topics discussed include: embedding text in hyperbolic spaces;scientific discovery as link prediction in influence and citation graphs;efficient generation and processing of word ...
ISBN:
(纸本)9781948087254
The proceedings contain 8 papers. The topics discussed include: embedding text in hyperbolic spaces;scientific discovery as link prediction in influence and citation graphs;efficient generation and processing of word co-occurrence networks using corpus2graph;multi-hop inference for sentence-level Textgraphs: how challenging is meaningfully combining information for science question answering?;multi-sentence compression with word vertex-labeled graphs and integer linear programming;large-scale spectral clustering using diffusion coordinates on landmark-based bipartite graphs;efficient graph-based word sense induction by distributional inclusion vector embeddings;fusing document, collection and label graph-based representations with word embeddings for text classification;and embedding text in hyperbolic spaces.
The proceedings contain 20 papers. The topics discussed include: bootstrapping large-scale fine-grained contextual advertising classifier from Wikipedia;modeling graph structure via relative position for text generati...
ISBN:
(纸本)9781954085381
The proceedings contain 20 papers. The topics discussed include: bootstrapping large-scale fine-grained contextual advertising classifier from Wikipedia;modeling graph structure via relative position for text generation from knowledge graphs;entity prediction in knowledge graphs with joint embeddings;hierarchical graph convolutional networks for jointly resolving cross-document coreference of entity and event mentions;learning clause representation from dependency-anchor graph for connective prediction;selective attention basedgraph convolutional networks for aspect-level sentiment classification;keyword extraction using unsupervised learning on the document’s adjacency matrix;improving human text simplification with sentence fusion;and on geodesic distances and contextual embedding compression for text classification.
Class imbalance is a prevalent issue in real-world graph-structure data, such as social and citation networks, posing significant challenges for graph Neural Networks (GNNs). Existing solutions often focus on balancin...
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The proceedings contain 16 papers. The topics discussed include: graph-based clustering for computational linguistics: a survey;towards the automatic creation of a wordnet from a term-based lexical network;an investig...
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ISBN:
(纸本)1932432779
The proceedings contain 16 papers. The topics discussed include: graph-based clustering for computational linguistics: a survey;towards the automatic creation of a wordnet from a term-based lexical network;an investigation on the influence of frequency on the lexical organization of verbs;robust and efficient page rank for word sense disambiguation;hierarchical spectral partitioning of bipartite graphs to cluster dialects and identify distinguishing features;a character-based intersection graph approach to linguistic phylogeny;spectral approaches to learning in the graph domain;and cross-lingual comparison between distributionally determined word similarity networks.
Pre-trained language Models (PLMs) are advanced technologies that enable deep-learning-based solutions for naturallanguageprocessing and understanding (NLP). They show exceptional results on general domain texts, bu...
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