SEQUEST: Mining frequent subsequences using DMA strips
MetadataShow full item record
Sequential patterns exist in data such as DNA string databases, occurrences of recurrent illness, etc. In this study, we present an algorithm, SEQUEST, to mine frequent subsequences from sequential patterns. The challenges of mining a very large database of sequences is computationally expensive and require large memory space. SEQUEST uses a Direct Memory Access Strips (DMA-Strips) structure to efficiently generate candidate subsequences. DMA-Strips structure provides direct access to each item to be manipulated and thus is optimized for speed and space performance. In addition, the proposed technique uses a hybrid principle of frequency counting by the vertical join approach and candidate generation by structure guided method. The structure guided method is adapted from the TMG approach used for enumerating subtrees in our previous work . Experiments utilizing very large databases of sequences which compare our technique with the existing technique, PLWAP , demonstrate the effectiveness of our proposed technique.
Showing items related by title, author, creator and subject.
Developing completion criteria for rehabilitation areas on arid and semi-arid mine sites in Western AustraliaBrearley, Darren (2003)Continued expansion of the gold and nickel mining industry in Western Australia during recent years has led to disturbance of larger areas and the generation of increasing volumes of waste rock. Mine operators are obligated ...
Song, Zhenhe (2008)In recent years oil and gas mining has moved into increasingly deeper water in search of undeveloped fields. As water depths approach and exceed 3000 m conventional offshore foundation systems become inefficient and ...
Cepuritis, Peter M. (2010)In order to develop an appropriate mine design, a thorough understanding of the rock mass conditions and its potential response to mining is required. Rock mass characterisation is a key component in developing models of ...