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  1. Proceedings of the 2nd international workshop on Patent information retrieval (PaIR '09)
  2. A case for probabilistic logic for scalable patent retrieval
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A case for probabilistic logic for scalable patent retrieval
Ontologies and semantic mining for bio-technology and chemistry data and patents
Extracting problem solved concepts from patent documents
Identification of low/high retrievable patents using content-based features
Phrase-based document categorization revisited
Interactive constrained clustering for patent document set
A design rationale representation model using patent documents
Automatic translation of scholarly terms into patent terms
Using normalized alignment scores to detect incorrectly aligned segments
On the role of classification in patent invalidity searches
Patent claim decomposition for improved information extraction
FindCite: automatically finding prior art patents

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A case for probabilistic logic for scalable patent retrieval

Content Provider ACM Digital Library
Author Azzam, Hany Roelleke, Thomas Klampanos, Iraklis A.
Abstract 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.
Starting Page 1
Ending Page 8
Page Count 8
File Format PDF
ISBN 9781605588094
DOI 10.1145/1651343.1651345
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2009-11-06
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Design Datalog Probabilistic Patent Modular Logic Db+ir
Content Type Text
Resource Type Article
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