• Dr. D. Mabuni

Clustering is an important task in machine learning and data mining. Similarity measures are used for data clustering. Jaccard similarity measure considers only full length sequences during similarity computation discarding partial sequences even though similarity is present in partial sequences also. To overcome this problem a new sequence similarity finding measure is proposed in this paper and this proposed similarity measure is used for clustering tree structures. Particularly in the trajectory data and medical data representations and management full length sequences will be considered for finding similarity between any two sequences. In such cases Jaccard is inefficient and proposed new technique is more efficient and effective for full length as well as partial length sequence similarity finding before data clustering.

partial length sequential branches, full length sequential branches, similarity between two trees, similarity between two structures, Jaccard similarity measure, similarity measures, Decision tree structures, Clustering.

"Sequence Clustering using Tree Structures", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.i661-i669, July-2023, Available :http://www.jetir.org/papers/JETIR2307895.pdf

"Sequence Clustering using Tree Structures", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppi661-i669, July-2023, Available at : http://www.jetir.org/papers/JETIR2307895.pdf