Automatic Generation of Event Ontology from Social Network and Mobile Positioning Data

Rajaonarivo, Landy; Mine, Tsunenori; Arakawa, Yutaka

doi:10.1145/3486622.3493933

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…The generation of the semantic knowledge graphs is described in our previous work [28]. This previous work consisted of automatically generating ontologies from tweets and representing the semantic information about POIs and the relationships between them via knowledge graphs.…”

Section: Proposed Approach a Global Architecturementioning

confidence: 99%

Little Known POI Category Estimation via Syntactical Knowledge Graph Generated via Tweets

Rajaonarivo,

Mine,

Arakawa

2023

2023 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)

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Local events are important for the vitality and dynamism of a city. However, some events or sites are lesserknown or only known by the local community. The information about them is then limited or not available. To address this issue, we propose an approach to automatically generate knowledge graphs from information posted on social networks and data on human mobility. This graph is generated from the tweets using the syntactic relationships between the verbs, nouns, and adjectives. Its exploitation would allow to estimate the categories of lesser-known points of Interest (POIs) or events. It can also allow to generate sentences and to answer questions that tourists may ask. The specificity of our approach lies in the Graph Convolutional Network (GCN)-based encoding of POIs with a graph of verbs, nouns, and adjectives and the estimation of POI categories using the proposed encoding. Experimental results show that our approach performs better than approaches in the literature.

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Section: Proposed Approach a Global Architecturementioning

confidence: 99%

Little Known POI Category Estimation via Syntactical Knowledge Graph Generated via Tweets

Rajaonarivo,

Mine,

Arakawa

2023

2023 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)

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“…We propose a data graph related to local events that is constructed by techniques handling syntactic and semantic data. The techniques using the semantic data consists in extracting information via an ontology that is automatically generated from tweets (without using references) and mobile positioning data [15], while the syntactic data analysis consists in determining the structures of sentences and converting them into a graph from verbs, nouns and particles. The data graph is then obtained by coupling the semantic graph and the syntactic graph.…”

Section: Related Workmentioning

confidence: 99%

“…3 presents some instances of the sub-class Food. The details of the automatic ontology generation approach and its evaluation via an online survey are described in [15].…”

Section: B Graph Generation: Use Case 1) Data Collectionmentioning

confidence: 99%

Coupling of semantic and syntactic graphs generated via tweets to detect local events

Rajaonarivo

Mine

Arakawa

2022

2022 12th International Congress on Advanced Applied Informatics (IIAI-AAI)

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Local events are important for the local people, tourists and local authorities. However, information about them is limited, or even absent on official websites. We propose an approach to automatically generate a data graph on local events via social network and mobile positioning data. This graph is constructed by the research results of syntactic and semantic data collection and will be used for an intelligent local event recommendation application. The coupling of these two research results makes it possible to discover little-known events or places that are not in the Linked Open Data and at the same time to connect them to it. An online experiment was set up to evaluate the performance of the techniques used in the study on semantic data which concerns the automatic ontology generation. The results allow us to conclude that the performance of the Named Entity Recognition and the choice of threshold score in automatic ontology generation depend on the categories of detected words types.

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Metodologias sobre aprendizagem de ontologias: uma revisão sistemática de literatura

Lopes,

Lima

2024

Revista Científica Multidisciplinar Núcleo do Conhecimento

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Contextualização: Ontologias vêm ganhando popularidade e reconhecimento em diferentes contextos. Entretanto, com o aumento exponencial de dados não estruturados na Web, o processo de construção de ontologias tornou-se complexo, demorado e dispendioso. Surgem, então, as abordagens de geração automática ou semiautomática de ontologias. Dado o contexto atual de transformação digital pelo qual passam diversos países, incluindo o Brasil, entende-se que as pesquisas sobre a automatização da geração de ontologias podem contribuir para a exploração e melhor aplicação desse tipo de Sistema de Organização do Conhecimento (SOC) no âmbito do governo eletrônico. Objetivo: Este estudo apresenta uma Revisão Sistemática da Literatura (RSL) sobre a geração automática e semiautomática de ontologias, com o objetivo de evidenciar o estágio atual da pesquisa nessa área. Métodos: Adotou-se o método proposto por Kitchenham (2004), que descreve procedimentos para realizar revisões sistemáticas de literatura, considerando a formulação de perguntas de pesquisa, o desenvolvimento de um protocolo, a identificação e seleção de estudos, avaliação de qualidade, extração e síntese de dados e relato dos resultados. Resultados: A revisão revelou uma diversidade significativa de abordagens e metodologias sendo exploradas para a geração automática e semiautomática de ontologias. No entanto muitas metodologias ainda enfrentam desafios, principalmente no que diz respeito ao detalhamento de fases e etapas que sejam facilmente replicáveis. Conclusões: Futuras pesquisas devem focar na criação de metodologias mais detalhadas e sistemáticas para aumentar a replicabilidade e a aplicação prática. As descobertas deste estudo podem inspirar investigações adicionais e estimular a implementação das ontologias no âmbito no governo eletrônico, com vistas a aprimorar a eficiência, a transparência e a acessibilidade dos serviços públicos digitais.

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Automatic Generation of Event Ontology from Social Network and Mobile Positioning Data

Cited by 3 publications

References 14 publications

Little Known POI Category Estimation via Syntactical Knowledge Graph Generated via Tweets

Little Known POI Category Estimation via Syntactical Knowledge Graph Generated via Tweets

Coupling of semantic and syntactic graphs generated via tweets to detect local events

Metodologias sobre aprendizagem de ontologias: uma revisão sistemática de literatura

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