Indexing dan Searching Document Menggunakan Metode Semantic Suffix Tree Clustering Berbasis Android
Anroid smartphone device has been involved in user’s way of living in this modern era. Smartphone device is used in user’s daily activity such as reading and storing electronic document in Pdf, Word and other file formats. User might and frequently forgot elctronic document’s directory in the smartphone.
This research aims to help user to find documents that reflect user’s keyword semantically or literally. Documents that reflect user keyword semantically or literaly will be shown. Various method is tested to minimize time use in clustering using suffix tree to semantic searching processes.
This research finds that user could find documents in the smartphone that reflect user’s keyword. Average time use for clustering about 100 documents containing 1000 word for each document is 686.7 seconds. User is able to search for document right after clustering process is done. Average time use for document searching is less than 2 seconds. Hence, thread implementation for processes decrease time consume greatly and the search result displayed to the user represents document content semantically.
Al-Anazi S., AlMahmoud H. & Al-Turaiki I. 2016. Finding similar documents using different clustering technique. Procedia Computer Science, 82 28–34
Janruan, J. & Guha. S. 2011. Semantic Suffix Tree Clustering. IEEE, 978-1-4244-8581-9/11, 35-40.
Liu, H., Bao, H. & Xu, D. 2011. Concept vector for semantic similarity and relatedness based on WordNet structur. The Journal of Systems and Software 85 (2012) 370– 381
Stopwords. Retrieved from Ranksnl website: http://www.ranks.nl/stopwords
Wei, T., Lu, Y., Chang, H,. Zhou, Q., & Bao, X,. 2014. A semantic approach for text clustering using WordNet and lexical chains. Expert Systems with Applications, 42 (2015) 2264–2275
Zamir, O. & Etzioni, O. 1998. Web Document Clustering: A Feasibility Demonstration. ACM, 1-58113-015-5 8/98
Zhuang, Y. & Chen, Y. 2015. Improving Suffix Tree Clustering Algorithm for Web Document. Atlantis Pres
- There are currently no refbacks.