Thou Shalt ASQFor and Shalt Receive the Semantic Answer
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 4264-4264.
Abstract
The combination of data, semantics, and the Web has led to an ever growing and increasingly complex body of semantic data. Accessing such structured data requires learning formal query languages, such as SPARQL, which poses significant difficulties for non-expert users. Many existing interfaces for querying Ontologies are based on approaches that rely on predefined templates and require expensive customization. To avoid the pitfalls of existing approaches, while at the same time retaining the ability to capture users' complex information needs, we have developed a simple keyword-based search interface to the Semantic Web. In this demonstration, we will present ASQFor, a systematic framework for automated SPARQL query formulation and execution over RDF repository using simple concept-based search primitives. Allowing end-users to express simple queries based on a list of key-value pairs that are then translated on-the-fly into SPARQL queries is a hard problem. In this demonstration, we will discuss the challenges that we have addressed to bring ASQFor to real practice, and also the difficult problems that remain to be solved in future work. During our demonstration, we will show how ASQFor can be used for decision support as well as an intelligent Q/A System.
@inproceedings{ijcai2016p652,
title = {Thou Shalt ASQFor and Shalt Receive the Semantic Answer},
author = {Saeed, Muhammad Rizwan and Chelmis, Charalampos and Prasanna, Viktor K.},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {4264--4264},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/652},
}
TY - CPAPER TI - Thou Shalt ASQFor and Shalt Receive the Semantic Answer AU - Saeed, Muhammad Rizwan AU - Chelmis, Charalampos AU - Prasanna, Viktor K. T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 4264 EP - 4264 UR - https://ijcai.org/proceedings/2016/652 ER -Copied
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