Sentence examples for mining algorithm extends from inspiring English sources

The following subsections describe how the proposed mining algorithm extends the classical association rule mining to acquire both intra- and inter-sentential language patterns.

Since the proposed mining algorithm is extended by the ant clustering algorithm of Deneubourg et al. [128],6 Ku-Mahamud modified the ant behavior of this ant clustering algorithm for big data clustering.

The algorithm extends our earlier algorithm MS-ELMA [34].

MEME algorithm extends the expectation maximization (EM) algorithm [ 38].

Sleuth [26] extends the ordered embedded pattern mining algorithm TreeMiner [27].

They introduce a discriminative subsequent mining to find optimal discriminative subsequent patterns, and extend the prefix span subsequence mining algorithm [33] in combination with LPBoost [34].

Therefore, this study develops a text mining framework by extending the classical association rule mining algorithm [ 24- 28] such that it can mine inter-sentential language patterns by associating frequently co-occurred patterns across the sentence boundary.

To acquire inter-sentential language patterns, we develop a text mining framework by extending the classical association rule mining algorithm such that it can discover frequently co-occurring patterns across the sentence boundary.

Fig. 4 Data mining algorithm.

Efficiency is achieved by designing the pattern mining algorithm as a hybrid of conventional pattern mining and graph data mining.

The data mining algorithm was introduced in the TMP.