Графтарды енгізу

method ID: graphembedding

Related Papers

Unsupervised Approaches for Automatic Keyword Extraction Using Meeting Transcripts

Authors: nan

Publication: TIPSTER (2009)

DOI: nan

This paper explores several unsupervised ap- proaches to automatic keyword extraction using meeting transcripts. In the TFIDF (term frequency, inverse document frequency) weighting framework, we incorporated part- of-speech (POS) information, …...

24006

Turning Distributional Thesauri into Word Vectors for Synonym Extraction and Expansion

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractIn this article, we propose to investigate a new problem consisting in turning a distributional thesaurus into dense word vectors. We propose more precisely a method for performing such task …...

7539

Graph Based Semi-Supervised Learning Approach for Tamil POS tagging

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

Parts of Speech (POS) tagging is an important pre-requisite for various Natural Language Processing tasks. POS tagging is rather challenging for morphologically rich languages such as Tamil. Being low-resourced, Tamil …...

17396

Disentangle-based Continual Graph Representation Learning

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractGraph embedding (GE) methods embed nodes (and/or edges) in graph into a low-dimensional semantic space, and have shown its effectiveness in modeling multi-relational data. However, existing GE models are not …...

30595

RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractMany graph embedding approaches have been proposed for knowledge graph completion via link prediction. Among those, translating embedding approaches enjoy the advantages of light-weight structure, high efficiency and great interpretability. …...

4311

Boosting Code Summarization by Embedding Code Structures

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractRecent research on code summarization relies on the structural information from the abstract syntax tree (AST) of source codes. It is, however, questionable whether it is the most effective to …...

4706

Combining ELECTRA and Adaptive Graph Encoding for Frame Identification

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractThis paper presents contributions in two directions: first we propose a new system for Frame Identification (FI), based on pre-trained text encoders trained discriminatively and graphs embedding, producing state of …...

16035