ML Anthology

Pragmatic Querying in Heterogeneous Knowledge Graphs

Amar Viswanathan
AAAI 2016 pp. 4317-4318
doi:10.1609/AAAI.V30I1.9819 /aaai/2016/viswanathan2016aaai-pragmatic/

Abstract

Knowledge Graphs with rich schemas can allow for complex querying. My thesis focuses on providing accessible Knowledge using Gricean notions of Cooperative Answering as a motivation. More specifically, using Query Reformulations, Data Awareness, and a Pragmatic Context, along with the results they can become more responsive to user requirements and user context.

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Cite

Text

Viswanathan. "Pragmatic Querying in Heterogeneous Knowledge Graphs." AAAI Conference on Artificial Intelligence, 2016. doi:10.1609/AAAI.V30I1.9819

Markdown

[Viswanathan. "Pragmatic Querying in Heterogeneous Knowledge Graphs." AAAI Conference on Artificial Intelligence, 2016.](https://mlanthology.org/aaai/2016/viswanathan2016aaai-pragmatic/) doi:10.1609/AAAI.V30I1.9819

BibTeX

@inproceedings{viswanathan2016aaai-pragmatic,
  title     = {{Pragmatic Querying in Heterogeneous Knowledge Graphs}},
  author    = {Viswanathan, Amar},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2016},
  pages     = {4317-4318},
  doi       = {10.1609/AAAI.V30I1.9819},
  url       = {https://mlanthology.org/aaai/2016/viswanathan2016aaai-pragmatic/}
}