A connectionist approach to conceptual information retrieval
ICAIL '87 Proceedings of the 1st international conference on Artificial intelligence and law
Conceptual information retrieval using RUBRIC
SIGIR '87 Proceedings of the 10th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
COREL: a conceptual retrieval system
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '89 Proceedings of the 12th annual international ACM SIGIR conference on Research and development in information retrieval
A neural network for probabilistic information retrieval
SIGIR '89 Proceedings of the 12th annual international ACM SIGIR conference on Research and development in information retrieval
CIKM '94 Proceedings of the third international conference on Information and knowledge management
A network approach to probabilistic information retrieval
ACM Transactions on Information Systems (TOIS)
A Model for Adaptive Information Retrieval
Journal of Intelligent Information Systems
Generating, integrating, and activating thesauri for concept-based document retrieval
IEEE Expert: Intelligent Systems and Their Applications
| Hi-index | 0.00 |
Knowledge Representation (KR) systems provide support for Artificial Intelligence systems that reason about relationships between objects in their domains of expertise. Because of their support for inference, KR systems appear to have potential to enrich the kind of retrievals that IR systems might make. Ironically, however, the most useful KR systems are limited to reasoning based on a rigid notion of validity, and thus are awkward to use when relevant but inexact retrievals are desired. We have been exploring the potential of a “connectionist” model—the Boltzmann Machine—to overcome this limitation. We report on a number of experiments in which we use a connectionist simulator to support similarity-based reasoning in a frame representation. We draw some tentative, mixed conclusions on the potential for a union of KR, IR, and connectionism.