In this paper, we will propose a domain ontology extensible method which can insert new keywords into the corresponding constructed domain ontology. The novel method uses TF-IDF (Term Frequency - Inverse Document Frequency) and LSA (Latent Semantic Analysis) to strengthen the semantic characteristic of keywords and transform the LSA matrix into a high dimensional space based on collected web pages. The similarity between keywords and concepts is evaluated by comparing the keywords on high dimensional matrix to the corresponding constructed ontology group center and individual concept. The keyword which has the highest similarity with the domain concept will be inserted into the offspring of the concept on the domain ontology and will become a new domain concept. The primary experiment uses the existing Chinese basketball ontology to examine its precision and the experimental results indicate that our proposed method has 73% accuracy.

A repeating pattern is commonly used in analyzing the repeated part of music data and looking for themes. Most of the repeating patterns are key melodies and are easy to familiarize and remember for people. Therefore, we can use the themes or the repeating patterns to construct indices that can speed up music retrieval. Non-trivial repeating patterns exclude those patterns which are all contained in other longer patterns, such that they can reduce the redundancy of the repeating patterns and save the index space. Most existing algorithms are time consuming for finding non-trivial repeating patterns. In this paper, we propose an approach for efficiently discovering nontrivial repeating patterns in linear time.

A consensus on a parallel architecture for very large database management has emerged. This architecture is based on a shared-nothing hardware organization. The computation model is very sensitive to skew in tuple distribution, however. The sorting operation is frequently used for database processing. For example sorting may be requested by users through the use of Distinct, Order By and Group By clauses in SQL. Although load balancing incurs processing costs, and therefore can have a profound influence on the optimized execution plan of a query, only few of the existing parallel sorting executions consider this factor. We present two parallel sorting algorithms using the dynamic load balancing technique to address the data skew problem. Our performance study indicates that the proposed parallel sorting techniques can provide very impressive performance improvement over conventional approaches.