Difference between revisions of "Exploring Semantically-Related Concepts from Wikipedia: the Case of Sere"
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== Overview == | == Overview == | ||
In this paper authors present web application SeRE designed to explore semantically related concepts. [[Wikipedia]] and [[DBpedia]] are rich data sources to extract related entities for a given topic, like in- and out-links, broader and narrower terms, categorisation information etc. Authors use the Wikipedia full text body to compute the semantic [[relatedness]] for extracted terms, which results in a list of entities that are most relevant for a topic. For any given query, the user interface of SeRE visualizes these related concepts, ordered by semantic relatedness; with snippets from Wikipedia articles that explain the connection between those two entities. In a user study authors examine how SeRE can be used to find important entities and their relationships for a given topic and to answer the question of how the classification system can be used for filtering. | In this paper authors present web application SeRE designed to explore semantically related concepts. [[Wikipedia]] and [[DBpedia]] are rich data sources to extract related entities for a given topic, like in- and out-links, broader and narrower terms, categorisation information etc. Authors use the Wikipedia full text body to compute the semantic [[relatedness]] for extracted terms, which results in a list of entities that are most relevant for a topic. For any given query, the user interface of SeRE visualizes these related concepts, ordered by semantic relatedness; with snippets from Wikipedia articles that explain the connection between those two entities. In a user study authors examine how SeRE can be used to find important entities and their relationships for a given topic and to answer the question of how the classification system can be used for filtering. | ||
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| + | == Embed == | ||
| + | === Wikipedia Quality === | ||
| + | <code> | ||
| + | <nowiki> | ||
| + | Hienert, Daniel; Wegener, Dennis; Schomisch, Siegfried. (2015). "[[Exploring Semantically-Related Concepts from Wikipedia: the Case of Sere]]". | ||
| + | </nowiki> | ||
| + | </code> | ||
| + | |||
| + | === English Wikipedia === | ||
| + | <code> | ||
| + | <nowiki> | ||
| + | {{cite journal |last1=Hienert |first1=Daniel |last2=Wegener |first2=Dennis |last3=Schomisch |first3=Siegfried |title=Exploring Semantically-Related Concepts from Wikipedia: the Case of Sere |date=2015 |url=https://wikipediaquality.com/wiki/Exploring_Semantically-Related_Concepts_from_Wikipedia:_the_Case_of_Sere}} | ||
| + | </nowiki> | ||
| + | </code> | ||
| + | |||
| + | === HTML === | ||
| + | <code> | ||
| + | <nowiki> | ||
| + | Hienert, Daniel; Wegener, Dennis; Schomisch, Siegfried. (2015). &quot;<a href="https://wikipediaquality.com/wiki/Exploring_Semantically-Related_Concepts_from_Wikipedia:_the_Case_of_Sere">Exploring Semantically-Related Concepts from Wikipedia: the Case of Sere</a>&quot;. | ||
| + | </nowiki> | ||
| + | </code> | ||
Revision as of 22:33, 24 September 2020
Authors | Daniel Hienert Dennis Wegener Siegfried Schomisch |
|---|---|
Publication date | 2015 |
Links | Original Preprint |
Exploring Semantically-Related Concepts from Wikipedia: the Case of Sere - scientific work related to Wikipedia quality published in 2015, written by Daniel Hienert, Dennis Wegener and Siegfried Schomisch.
Overview
In this paper authors present web application SeRE designed to explore semantically related concepts. Wikipedia and DBpedia are rich data sources to extract related entities for a given topic, like in- and out-links, broader and narrower terms, categorisation information etc. Authors use the Wikipedia full text body to compute the semantic relatedness for extracted terms, which results in a list of entities that are most relevant for a topic. For any given query, the user interface of SeRE visualizes these related concepts, ordered by semantic relatedness; with snippets from Wikipedia articles that explain the connection between those two entities. In a user study authors examine how SeRE can be used to find important entities and their relationships for a given topic and to answer the question of how the classification system can be used for filtering.
Embed
Wikipedia Quality
Hienert, Daniel; Wegener, Dennis; Schomisch, Siegfried. (2015). "[[Exploring Semantically-Related Concepts from Wikipedia: the Case of Sere]]".
English Wikipedia
{{cite journal |last1=Hienert |first1=Daniel |last2=Wegener |first2=Dennis |last3=Schomisch |first3=Siegfried |title=Exploring Semantically-Related Concepts from Wikipedia: the Case of Sere |date=2015 |url=https://wikipediaquality.com/wiki/Exploring_Semantically-Related_Concepts_from_Wikipedia:_the_Case_of_Sere}}
HTML
Hienert, Daniel; Wegener, Dennis; Schomisch, Siegfried. (2015). "<a href="https://wikipediaquality.com/wiki/Exploring_Semantically-Related_Concepts_from_Wikipedia:_the_Case_of_Sere">Exploring Semantically-Related Concepts from Wikipedia: the Case of Sere</a>".
