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Case Retrieval, Hashing Indexing, Sequential Indexing, Case Base Reasoning

The main objective of case retrieval is to scan and to map the most similar old cases in case base with a new problem. Beside accurateness, the time taken to retrieve case is also important. With the increasing number of cases in case base, the retrieval task is becoming more challenging where faster retrieval time and good accuracy are the main aim. Traditionally, sequential indexing method has been applied to search for possible cases in case base. This technique worked fast when the number of cases is small but requires more time to retrieve when the number of data in case base grows. As an alternative, this paper presents the integration of hashing indexing technique in case retrieval to mine large cases and speed up the retrieval time. Hashing indexing searches a record by determining the index using only an entry’s search key without traversing all records. To test the proposed method, real data namely Timah Tasoh Dam operational dataset, which is temporal in nature that represents the historical hydrological data of daily Timah Tasoh dam operation in Perlis, Malaysia ranging from year 1997-2005, was chosen as experiment. Then, the hashing indexing performance is compared with sequential method in term of retrieval time and accuracy. The finding indicates that hashing indexing is more accurate and faster than sequential approach in retrieving cases. Besides that, the combination of hashing search key x produces better result compared to single search key.