Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
A new methodology for systematic exploitation of technology databases
Information Processing and Management: an International Journal
WordNet: a lexical database for English
Communications of the ACM
A patent search and classification system
Proceedings of the fourth ACM conference on Digital libraries
ACM Computing Surveys (CSUR)
Using text processing techniques to automatically enrich a domain ontology
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
Knowledge discovery from texts: a concept frame graph approach
Proceedings of the eleventh international conference on Information and knowledge management
Knowledge discovery in patent databases
Proceedings of the eleventh international conference on Information and knowledge management
Nomograms for visualization of naive Bayesian classifier
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Using the patent co-citation approach to establish a new patent classification system
Information Processing and Management: an International Journal
The clustering power of low frequency words in academic Webs: Brief Communication
Journal of the American Society for Information Science and Technology
Text mining without document context
Information Processing and Management: an International Journal - Special issue: Informetrics
Self-associated concept mapping for representation, elicitation and inference of knowledge
Knowledge-Based Systems
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Patent databases provide valuable information for technology management. However, the rapid growth of patent documents, the lengthy text and the rich of content in technical terminology, and the complicated relationships among the patents, make it taking a lot of human effort for conducting analyses. As a result, an automated system for assisting the inventors in patent analysis as well as providing support in technological innovation is in great demand. In this paper, a Semantic-based Intellectual Property Management System (SIPMS) has been developed for supporting the management of intellectual properties (IP). It incorporates semantic analysis and text mining techniques for processing and analyzing the patent documents. The method differentiates itself from the traditional technological management tools in its knowledge base. Instead of eliciting knowledge from domain experts, the proposed method adopts global patent databases as sources of knowledge. The system enables users to search for existing patent documents or relevant IP documents which are related to a potential new invention and to support invention by providing the relationships and patterns among a group of IP documents. The method has been evaluated by benchmarking with the performance against traditional text mining technique and has successfully been implemented at a selected reference site.