On querying simple conceptual graphs with negation
Data & Knowledge Engineering
Knowledge formalization in experience feedback processes: An ontology-based approach
Computers in Industry
Text Retrieval Oriented Auto-construction of Conceptual Relationship
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part II
Query-Answering CG Knowledge Bases
ICCS '08 Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning
Knowledge and Information Systems
A structural computing approach to the production of multimedia document series
The New Review of Hypermedia and Multimedia
Bayesian network based business information retrieval model
Knowledge and Information Systems
An easy way of expressing conceptual graph queries from keywords and query patterns
ICCS'10 Proceedings of the 18th international conference on Conceptual structures: from information to intelligence
Expressing conceptual graph queries from patterns: how to take into account the relations
ICCS'11 Proceedings of the 19th international conference on Conceptual structures for discovering knowledge
Continuous improvement through knowledge-guided analysis in experience feedback
Engineering Applications of Artificial Intelligence
Large-margin feature selection for monotonic classification
Knowledge-Based Systems
A semantic web interface using patterns: the SWIP system
GKR'11 Proceedings of the Second international conference on Graph Structures for Knowledge Representation and Reasoning
Incomplete and fuzzy conceptual graphs to automatically index medical reports
NLDB'07 Proceedings of the 12th international conference on Applications of Natural Language to Information Systems
The bootstrapping based recognition of conceptual relationship for text retrieval
NLDB'07 Proceedings of the 12th international conference on Applications of Natural Language to Information Systems
Allowing end users to query graph-based knowledge bases
EKAW'12 Proceedings of the 18th international conference on Knowledge Engineering and Knowledge Management
Engineering Applications of Artificial Intelligence
| Hi-index | 0.00 |
An intelligent information retrieval system is presented in this paper. In our approach, which complies with the logical view of information retrieval, queries, document contents and other knowledge are represented by expressions in a knowledge representation language based on the conceptual graphs introduced by Sowa. In order to take the intrinsic vagueness of information retrieval into account, i.e. to search documents imprecisely and incompletely represented in order to answer a vague query, different kinds of probabilistic logic are often used. The search process described in this paper uses graph transformations instead of probabilistic notions. This paper is focused on the content-based retrieval process, and the cognitive facet of information retrieval is not directly addressed. However, our approach, involving the use of a knowledge representation language for representing data and a search process based on a combinatorial implementation of van Rijsbergen’s logical uncertainty principle, also allows the representation of retrieval situations. Hence, we believe that it could be implemented at the core of an operational information retrieval system. Two applications, one dealing with academic libraries and the other concerning audiovisual documents, are briefly presented.