Graph-based text representation and matching: A review of the state of the art and future challenges
AH Osman, OM Barukub - IEEE Access, 2020 - ieeexplore.ieee.org
Graph-based text representation is one of the important preprocessing steps in data and text
mining, Natural Language Processing (NLP), and information retrieval approaches. The …
mining, Natural Language Processing (NLP), and information retrieval approaches. The …
Frequent approximate subgraphs as features for graph-based image classification
N Acosta-Mendoza, A Gago-Alonso… - Knowledge-Based …, 2012 - Elsevier
The use of approximate graph matching for frequent subgraph mining has been identified in
different applications as a need. To meet this need, several algorithms have been …
different applications as a need. To meet this need, several algorithms have been …
New approaches to extract information from posts on COVID-19 published on Reddit
In the last two years, we have seen a huge number of debates and discussions on COVID-
19 in social media. Many authors have analyzed these debates on Facebook and Twitter …
19 in social media. Many authors have analyzed these debates on Facebook and Twitter …
Unraveling traveler mobility patterns and predicting user behavior in the Shenzhen metro system
C Yang, F Yan, SV Ukkusuri - Transportmetrica A: Transport …, 2018 - Taylor & Francis
Over the last few years, cities have made available large volumes of smart card data that
shed light on the urban dynamics of transit users. This research uses metro card data from …
shed light on the urban dynamics of transit users. This research uses metro card data from …
Assessing urban travel patterns: An analysis of traffic analysis zone-based mobility patterns
Y Chen, Z Zhang, T Liang - Sustainability, 2019 - mdpi.com
Information and communication technology development has yielded large-scale
spatiotemporal datasets, such as mobile phone, automatic collection system, and car-hailing …
spatiotemporal datasets, such as mobile phone, automatic collection system, and car-hailing …
Daily metro origin-destination pattern recognition using dimensionality reduction and clustering methods
C Yang, F Yan, X Xu - 2017 IEEE 20th International Conference …, 2017 - ieeexplore.ieee.org
Widespread usage of Smart Cards is leading to unprecedentedly massive growth of the
quantity of data. However, traditional methods still fail to fully recognize mobility patterns and …
quantity of data. However, traditional methods still fail to fully recognize mobility patterns and …
A survey of document clustering using semantic approach
NY Saiyad, HB Prajapati… - … Conference on Electrical …, 2016 - ieeexplore.ieee.org
Document clustering is the application of cluster analysis to textual documents. It is
commonly used technique in data mining, information retrieval, knowledge discovery from …
commonly used technique in data mining, information retrieval, knowledge discovery from …
REAFUM: representative approximate frequent subgraph mining
Noisy graph data and pattern variations are two thorny problems faced by mining frequent
subgraphs. Traditional exact-matching based methods, however, only generate patterns that …
subgraphs. Traditional exact-matching based methods, however, only generate patterns that …
A new proposal for graph-based image classification using frequent approximate subgraphs
A Morales-Gonzalez, N Acosta-Mendoza… - Pattern Recognition, 2014 - Elsevier
Graph-based data representations are an important research topic due to the suitability of
this kind of data structure to model entities and the complex relations among them. In …
this kind of data structure to model entities and the complex relations among them. In …
Semantic-based text document clustering using cognitive semantic learning and graph theory
Semantic-based text document clustering aims to group documents into a set of topic
clusters. We propose a new approach for semantically clustering of text documents based …
clusters. We propose a new approach for semantically clustering of text documents based …