By searching for any query term on the premise that there are errors in the recognized text, the methods presented can tolerate such errors, and therefore manual post-editing is not required after OCR recognition. In the applied approach, confusion matrices are used to store characters which are likely to be interchanged when a particular character is missrecognized, and the respective probability of each occurrence. Multiple search terms are generated for an input query term by making reference to confusion matrices, after which a full-text search is run for each search term. Those with a validity value greater than a given threshold are judged to satisfy the input query. In addition, the performance of these methods is experimentally evaluated by determining retrieval effectiveness, i.e., by calculating recall and precision rates.
Results indicate marked improvement in comparison with exact matching.
Some applications requiring very high QoS, and the progresses in IC technology and processing capacity make it possible to introduce ARQ mechanism in high-speed ATM networks economically and efficiently. In this paper, an ARQ scheme based on selective repeat strategy is proposed. Its performance in terms of throughput, traffic increment and required buffer size is evaluated by both theoretical analysis and simulation. The analytical and simulation results show that the proposed scheme has a very good error detection capability while maintaining high throughput with an acceptable requirement of buffer size. To study the performance of an ATM network, it is necessary to consider an analysis model that can take general traffic model into account since the network can provide service to various types of sources.