SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
Text Information Retrieval Systems
Text Information Retrieval Systems
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Automatic Information Organization and Retrieval.
Automatic Information Organization and Retrieval.
Sentence Similarity Based on Semantic Nets and Corpus Statistics
IEEE Transactions on Knowledge and Data Engineering
Grouping of TRIZ Inventive Principles to facilitate automatic patent classification
Expert Systems with Applications: An International Journal
A substance-field ontology to support the TRIZ thinking approach
International Journal of Computer Applications in Technology
Parameter network as a means for driving problem solving process
International Journal of Computer Applications in Technology
Distributional measures of concept-distance: a task-oriented evaluation
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
An integrated parameterized tool for designing a customized tracheal stent
Computer-Aided Design
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The theory of inventive problem solving TRIZ was developed to solve inventive problems in different industrial fields. In recent decades, modern innovation theories and methods proposed several different knowledge sources. These knowledge sources are all built independently of the specific application and their different levels of abstraction make it quite difficult to use them without extensive knowledge about different engineering domains. Considering that all the TRIZ knowledge sources are described in short-text, the missing links among the TRIZ knowledge sources are defined based on short-text semantic similarity, which also makes it possible to ease the use of TRIZ. Meanwhile, the ontology reasoning mechanism deployed on Protégé and JESS, is used to provide heuristic solutions dynamically for TRIZ users. Firstly, TRIZ users start solving the inventive problem with the TRIZ knowledge source of their choice. Then other similar knowledge sources are obtained according to a calculation of semantic relatedness. Finally, with the help of the heuristic abstract solutions and pointers to physical-chemical-geometrical effects, specific solutions are obtained through ontology reasoning. A particular case of a "Diving Fin" is studied to show the heuristic processes of searching abstract solutions and pointers to physical-chemical-geometrical effects in detail.