Q) What is #KnowledgeGraph #Exploration?
A) a machine-assisted process of analysis of a KG to: (1) understand its structure (2) identify whether it can satisfy the current information need and (3) locate the portion of the KG pertinent to the current need
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A) a machine-assisted process of analysis of a KG to: (1) understand its structure (2) identify whether it can satisfy the current information need and (3) locate the portion of the KG pertinent to the current need
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In this work we divide techniques in:
a) Summarization/Profiling
b) Exploratory Analytics
c) Exploratory Search
These 3 are mapped on a spectrum from no interaction and no requirement to domain knowledge, to high interaction and higher requirement of domain knowledge.
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a) Summarization/Profiling
b) Exploratory Analytics
c) Exploratory Search
These 3 are mapped on a spectrum from no interaction and no requirement to domain knowledge, to high interaction and higher requirement of domain knowledge.
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Less interactive methods require less domain knowledge, the system is doing all the work given some general definition of "interestingness". Yet, they also produce less detailed answers.
More interactive approaches require more domain knowledge, but can provide more details.
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More interactive approaches require more domain knowledge, but can provide more details.
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So what's next? Interactive Exploratory Analytics.
We need methods that are more user-friendly and scalable. We also need to think out of the box: traditional multi-dimensional analysis is good for tabular data, we are dealing with complex structures.
See edao.eu
We need methods that are more user-friendly and scalable. We also need to think out of the box: traditional multi-dimensional analysis is good for tabular data, we are dealing with complex structures.
See edao.eu
@threadreaderapp please unroll
