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Web catalog integration has become an integral aspect of current digital content management for Internet and e-commerce environments. The Web catalog integration problem concerns integration of documents in a source catalog into a destination catalog. Many investigations have focused on flattened (one-dimensional) catalogs, but few works address hierarchical Web catalog integration. This study presents a hierarchical catalog integration (EHCI) approach based on the conceptual thesauri extracted from the source catalog and the destination catalog to improve performance. Experiments involving real-world catalog integration are performed to measure the performance of the improved hierarchical catalog integration scheme. Experimental results demonstrate that the EHCI approach consistently improves the average accuracy performance of each hierarchical category.

In software testing and maintenance activities, the observed faults and bugs are reported in bug report managing systems (BRMS) for further analysis and repair. According to the information provided by bug reports, developers need to find out the location of these faults and fix them. However, bug locating usually involves intensively browsing back and forth through bug reports and software code and thus incurs unpredictable cost of labor and time. Hence, establishing a robust model to efficiently and effectively locate and track faults is crucial to facilitate software testing and maintenance. In our observation, some related bug locations are tightly associated with the implicit links among source files. In this paper, we present an implicit social network model using PageRank to establish a social network graph with the extracted links. When a new bug report arrives, the prediction model provides users with likely bug locations according to the implicit social network graph constructed from the co-cited source files. The proposed approach has been implemented in real-world software archives and can effectively predict correct bug locations.

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