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Text graph

In natural language processing (NLP), a text graph is a graph representation of a text item (document, passage or sentence). It is typically created… 
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Related topics

Related topics

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Bag-of-words modelDocument classificationDocument-term matrixEmpirical Methods in Natural Language Processing

Broader (1)

Natural language processing

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Dependency-based Text Graphs for Keyphrase and Summary Extraction with Applications to Interactive Content Retrieval
We build a bridge between neural network-based machine learning and graph-based natural language processing and introduce a… 
2017
2017
Co-reference resolution in graph model for enhancing vietnamese paragraph compression
Text compression based on graph representation model (referred to as “text graph”) is a fairly common approach. However, one of… 
2016
2016
Thematic Text Graph: A Text Representation Technique for Keyword Weighting in Extractive Summarization System
Keyword extraction approaches based on directed graph representation of text mostly use word positions in the sentences. A… 
2015
2015
Mining Tasks from the Web Anchor Text Graph: MSR Notebook Paper for the TREC 2015 Tasks Track
Abstract : Users may have a variety of tasks that give rise to issuing a particular query. The goal of the Tasks Track at… 
Review
2014
Review
2014
Centrality Measures for Non-Contextual Graph-Based Unsupervised Single Document Keyword Extraction
The manner in which keywords fulfill the role of being central to a document is frustratingly still an open question. In this… 
2009
2009
Query-Oriented Summarization Based on Neighborhood Graph Model
In this paper, we investigate how to combine the link-aware and link-free information in sentence ranking for query-oriented… 
2008
2008
Improved Approximate Pattern Matching on Hypertext
The problem of approximate pattern matching on hypertext is deened and solved by Amir et al. in O(m(n log m + e)) time, where m… 
2007
2007
Timestamped Graphs: Evolutionary Models of Text for Multi-Document Summarization
Current graph-based approaches to automatic text summarization, such as LexRank and TextRank, assume a static graph which does… 
2007
2007
NUS at DUC 2007: Using Evolutionary Models of Text
This paper presents our new, querybased multi-document summarization system used in DUC 2007. Current graph-based approaches to… 
2005
2005
A Graph-Based Rule-Mining Framework for Natural Language Learning and Understanding
Learning and understanding natural languages are usually considered as independent tasks in natural language processing. These… 
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