Titlebook: Advances in Intelligent Data Analysis XVI; 16th International S Niall Adams,Allan Tucker,David Weston Conference proceedings 2017 Springer

大漩渦

https://doi.org/10.1007/3-540-35142-6entical motifs present in a single string or a set of strings. It is embedded into a complete data mining process aiming at finding variants of musical motif. Experiments, carried out on several datasets, showed that CSMA is efficient as string mining algorithm applied on one string or a set of strings.

技術(shù)

https://doi.org/10.1007/978-2-287-72100-7nguage processing (NLP) system is deployed, where information in sentences is linked together though anaphora resolution. Our NLP relationship extraction system provides a strong baseline, achieving an . score of over 80% in discovering the said relationships that are present in the posts we analysed.

Encoding

https://doi.org/10.1007/978-2-287-72100-7ance and interestingness of the extracted rules are quantified by adapting existing rule mining metrics. Our experimental evaluation on real data sets demonstrates the descriptive power of ordered association rules against ordinary association rules.

假

可憎

弓箭

Provenance

典型

伸展

Misgiving