Searching distributed collections with inference networks
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic Datalog—a logic for powerful retrieval methods
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
A decision-theoretic approach to database selection in networked IR
ACM Transactions on Information Systems (TOIS)
Server selection on the World Wide Web
DL '00 Proceedings of the fifth ACM conference on Digital libraries
A language modeling framework for resource selection and results merging
Proceedings of the eleventh international conference on Information and knowledge management
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Server selection methods in hybrid portal search
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
The VLDB Journal — The International Journal on Very Large Data Bases
Scaling up high-value retrieval to medium-volume data
IRFC'10 Proceedings of the First international Information Retrieval Facility conference on Adbances in Multidisciplinary Retrieval
| Hi-index | 0.00 |
Patent searching is a complex retrieval task. An initial document search is only the starting point of a chain of searches and decisions that need to be made by patent searchers. Keyword-based retrieval is adequate for document searching, but it is not suitable for modelling comprehensive retrieval strategies. DB-like and logical approaches are the state-of-the-art techniques to model strategies, reasoning and decision making. In this paper we present the application of logical retrieval to patent searching. The two grand challenges are expressiveness and scalability, where high degree of expressiveness usually means a loss in scalability. In this paper we report how to maintain scalability while offering the expressiveness of logical retrieval required for solving patent search tasks. We present logical retrieval background, and how to model data-source selection and results’ fusion. Moreover, we demonstrate the modelling of a retrieval strategy, a technique by which patent professionals are able to express, store and exchange their strategies and rationales when searching patents or when making decisions. An overview of the architecture and technical details complement the paper, while the evaluation reports preliminary results on how query processing times can be guaranteed, and how quality is affected by trading off responsiveness.