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Everything about Text graph
Text-structure representation using graph models
In natural language processing (NLP), a text graph is a graph representation of a text item. It is typically created as a preprocessing step to support NLP tasks such as text condensation term disambiguation (topic-based) text summarization, relation extraction and textual entailment. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Text graphA 5-minute orientation
- Skim a recent paper: Graph neural networks for text classification: a surveyInfluential work since 2022
- Pick up a classic book: Fundamentals of Computer Programming with CSharp Free Book (by Nakov & Co.)The most-reprinted book on the subject
- Read the landmark paper: MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reportsCited 1,808 times
- Go sideways: Knowledge extractionA closely related topic
- Go sideways: Ontology learningA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports
Graph Convolutional Networks for Text Classification
Tensor Graph Convolutional Networks for Text Classification
Graph Fusion Network for Text Classification
$\text{RD}\small{\text{YN}}$ : graph benchmark handling community dynamics
Text FCG: Fusing Contextual Information via Graph Learning for text classification
AMR-To-Text Generation with Graph Transformer
Graph-based abstractive biomedical text summarization
🆕 Influential since 2022
Graph neural networks for text classification: a survey
Text-instance graph: Exploring the relational semantics for text-based visual question answering
Image-text interaction graph neural network for image-text sentiment analysis
Extractive Arabic Text Summarization-Graph-Based Approach
Transformer and Graph Convolutional Network for Text Classification
📚 Books worth reading
Fundamentals of Computer Programming with CSharp Free Book (by Nakov & Co.)Svetlin Nakov · 2013
Combinatorial Pattern Matching 19th Annual Symposium Cpm 2008 Pisa Italy June 1820 2008 ProceedingsPaolo Ferragina · 2008
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Knowledge extraction Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources. The resulting…
- Ontology learning Ontology learning (ontology extraction, ontology augmentation generation, ontology generation, or ontology acquisition) is the automatic or semi-automatic…
- Natural language processing Natural language processing (NLP) is the processing of natural language information by a computer. NLP is a subfield of computer science and is closely…
- Information extraction Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents…
- Automatic summarization Automatic summarization is the process of shortening a set of data computationally, to create a subset (a summary) that represents the most important or…
- Knowledge graph In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate…
- Multimedia information retrieval Multimedia information retrieval (MMIR or MIR) is a research discipline of computer science that aims at extracting semantic information from multimedia…
- Semantic parsing Semantic parsing is the task of converting a natural language utterance to a logical form: a machine-understandable representation of its meaning. Semantic…