Romão Martines - Academia.edu (original) (raw)
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Papers by Romão Martines
Data published on the Web is growing every year. However, most of this data does not have semanti... more Data published on the Web is growing every year. However, most of this data does not have semantic representation. Web tables are an example of structured data on the Web that has no clear semantics. While there is an emerging research effort in lifting tabular data into semantic web formats, most of the work is focused around entity recognition in tables with simple structure. In this work we explore how capture the semantics of complex tables and transform them to knowledge graph. These complex tables include contextual information about statements, such as time or provenance. Hence, we need to use contextualized knowledge graphs to represent the information of the tables. We explore how this contextual information is represented in tables, and relate it to previous classifications of web tables, and how to encode it in RDF using different approaches. Finally, we present a prototype tool that converts web tables from Wikipedia into RDF, trying to cover all existing approaches.
Data published on the Web is growing every year. However, most of this data does not have semanti... more Data published on the Web is growing every year. However, most of this data does not have semantic representation. Web tables are an example of structured data on the Web that has no clear semantics. While there is an emerging research effort in lifting tabular data into semantic web formats, most of the work is focused around entity recognition in tables with simple structure. In this work we explore how capture the semantics of complex tables and transform them to knowledge graph. These complex tables include contextual information about statements, such as time or provenance. Hence, we need to use contextualized knowledge graphs to represent the information of the tables. We explore how this contextual information is represented in tables, and relate it to previous classifications of web tables, and how to encode it in RDF using different approaches. Finally, we present a prototype tool that converts web tables from Wikipedia into RDF, trying to cover all existing approaches.
Data published on the Web is growing every year. However, most of this data does not have semanti... more Data published on the Web is growing every year. However, most of this data does not have semantic representation. Web tables are an example of structured data on the Web that has no clear semantics. While there is an emerging research effort in lifting tabular data into semantic web formats, most of the work is focused around entity recognition in tables with simple structure. In this work we explore how capture the semantics of complex tables and transform them to knowledge graph. These complex tables include contextual information about statements, such as time or provenance. Hence, we need to use contextualized knowledge graphs to represent the information of the tables. We explore how this contextual information is represented in tables, and relate it to previous classifications of web tables, and how to encode it in RDF using different approaches. Finally, we present a prototype tool that converts web tables from Wikipedia into RDF, trying to cover all existing approaches.
Data published on the Web is growing every year. However, most of this data does not have semanti... more Data published on the Web is growing every year. However, most of this data does not have semantic representation. Web tables are an example of structured data on the Web that has no clear semantics. While there is an emerging research effort in lifting tabular data into semantic web formats, most of the work is focused around entity recognition in tables with simple structure. In this work we explore how capture the semantics of complex tables and transform them to knowledge graph. These complex tables include contextual information about statements, such as time or provenance. Hence, we need to use contextualized knowledge graphs to represent the information of the tables. We explore how this contextual information is represented in tables, and relate it to previous classifications of web tables, and how to encode it in RDF using different approaches. Finally, we present a prototype tool that converts web tables from Wikipedia into RDF, trying to cover all existing approaches.