Language Modeling for Information Retrieval
Language Modeling for Information Retrieval
The Journal of Machine Learning Research
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Proposal of two-stage patent retrieval method considering the claim structure
ACM Transactions on Asian Language Information Processing (TALIP)
LDA-based document models for ad-hoc retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Information Processing and Management: an International Journal
Enhancing patent retrieval by citation analysis
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Information Retrieval
Introduction to Information Retrieval
Toward a more rational patent search paradigm
Proceedings of the 1st ACM workshop on Patent information retrieval
A Comparative Study of Utilizing Topic Models for Information Retrieval
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Automatic query generation for patent search
Proceedings of the 18th ACM conference on Information and knowledge management
Search system requirements of patent analysts
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Personalized topic-based tag recommendation
Neurocomputing
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The availability of large volumes of granted patents and applications, all publicly available on the Web, enables the use of sophisticated text mining and information retrieval methods to facilitate access and analysis of patents. In this paper we investigate techniques to automatically recommend patents given a query patent. This task is critical for a variety of patent-related analysis problems such as finding relevant citations, research of relevant prior art, and infringement analysis. We investigate the use of latent Dirichlet allocation and Dirichlet multinomial regression to represent patent documents and to compute similarity scores. We compare our methods with state-of-the-art document representations and retrieval techniques and demonstrate the effectiveness of our approach on a collection of US patent publications.