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
ECIR'07 Proceedings of the 29th European conference on IR research
Ranking-based processing of SQL queries
Proceedings of the 20th ACM international conference on Information and knowledge management
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Patent retrieval has emerged as an important application of information retrieval. Inherent properties of patent searching, such as large corpora, document length and the use of terminology have created the need for alternative approaches to searching. Logic-based information retrieval, as it is modelled by DB+IR systems, can accommodate these needs through its power of abstraction and the use of database-friendly query languages. However, there is a trade-off between expressiveness and efficiency. We propose to tackle such efficiency issues through distribution and parallelisation. In this paper we present our arguments in favour of a parallelised patent searching solution built on top of a probabilistic DB+IR system. Our contributions are both conceptual as well as technical. We demonstrate the flexibility of this approach by modelling two resource selection algorithms in probabilistic logic, expressed in probabilistic Datalog -- a rule-based language designed for expressing database-related tasks. Then, we provide early experimental indications which support the feasibility and technical soundness of this approach.