Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal
Automatic structuring and retrieval of large text files
Communications of the ACM
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A patent search and classification system
Proceedings of the fourth ACM conference on Digital libraries
Collection selection and results merging with topically organized U.S. patents and TREC data
Proceedings of the ninth international conference on Information and knowledge management
A vector space model for automatic indexing
Communications of the ACM
Modern Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Information Processing and Management: an International Journal
Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data
Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data
Cluster-based patent retrieval
Information Processing and Management: an International Journal
Patent document categorization based on semantic structural information
Information Processing and Management: an International Journal
Text mining techniques for patent analysis
Information Processing and Management: an International Journal
A similarity-based method for retrieving documents from the SCI/SSCI database
Journal of Information Science
Patent surrogate extraction and evaluation in the context of patent mapping
Journal of Information Science
Visualization of patent analysis for emerging technology
Expert Systems with Applications: An International Journal
Structure clustering for Chinese patent documents
Expert Systems with Applications: An International Journal
Text Clustering with Feature Selection by Using Statistical Data
IEEE Transactions on Knowledge and Data Engineering
Patent search using IPC classification vectors
Proceedings of the 4th workshop on Patent information retrieval
A proposed IPC-Based clustering and applied to technology strategy formulation
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part II
Vector space model for patent documents with hierarchical class labels
Journal of Information Science
Creating a Taxonomy for Mobile Commerce Innovations Using Social Network and Cluster Analyses
International Journal of Electronic Commerce
CV-PCR: a context-guided value-driven framework for patent citation recommendation
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Cross-language patent matching via an international patent classification-based concept bridge
Journal of Information Science
Journal of Information Science
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Determining requirements when searching for and retrieving relevant information suited to a user's needs has become increasingly important and difficult, partly due to the explosive growth of electronic documents. The vector space model (VSM) is a popular method in retrieval procedures. However, the weakness in traditional VSM is that the indexing vocabulary changes whenever changes occur in the document set, or the indexing vocabulary selection algorithms, or parameters of the algorithms, or if wording evolution occurs. The major objective of this research is to design a method to solve the afore-mentioned problems for patent retrieval. The proposed method utilizes the special characteristics of the patent documents, the International Patent Classification (IPC) codes, to generate the indexing vocabulary for presenting all the patent documents. The advantage of the generated indexing vocabulary is that it remains unchanged, even if the document sets, selection algorithms, and parameters are changed, or if wording evolution occurs. Comparison of the proposed method with two traditional methods (entropy and chi-square) in manual and automatic evaluations is presented to verify the feasibility and validity. The results also indicate that the IPC-based indexing vocabulary selection method achieves a higher accuracy and is more satisfactory.