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An Optimization for Hybrid Semantic Similarity Computation
Zhixiao Wang,Xiaofang Ding,Ying Huang 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.10
Semantic similarity computation is of great importance in many applications such as natural language processing, knowledge acquisition and information retrieval. In recent years, many concept similarity measures have been developed for ontology and lexical taxonomy. Generally speaking, ontology concepts semantic similarity computation is tedious and time-consuming. This paper puts forward an optimization algorithm to simplify semantic similarity computation. The optimization algorithm utilizes hierarchical relationship between concepts to simplify similarity computation process. Simulation experiments showed the optimization algorithm could make similarity computation simple and convenient, and similarity computation speed was improved by one time. The more complexity an ontology structure, and the bigger the maximum depth of ontology, the more significantly the performance improved.
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Community-based Collaborative Filtering Recommendation Algorithm
Xiaofang Ding,Zhixiao Wang,Shaoda Chen,Ying Huang 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.2
Collaborative filtering recommendation technology is by far the most widely used and successful personalized recommendation technology. However, the method currently faced with some problems such as sparse matrix, affecting the accuracy of the predicted results. This paper puts forward a new community detection algorithm based on topological potential theory, and combines it with collaborative filtering recommendation algorithm. The users with similar interests are put into the same community. When searching for the user’s nearest neighbor, it target to the users in a specific community or several communities instead of all users, which narrows the search and improves the prediction accuracy. Experimental results suggest that this approach effectively reduces the impact on the prediction accuracy of the sparse matrix, and significantly improves the prediction ability and recommendation quality.
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Xiaoting Song,Ailu Wu,Zhixiao Ding,Shixiong Liang,Chunyan Zhang 대한암학회 2020 Cancer Research and Treatment Vol.52 No.3
Purpose The purpose of this study was to evaluate the diagnostic value of soluble Axl (sAxl) in hepatocellular carcinoma (HCC) in comparison with serum "-fetoprotein (AFP). Materials and Methods Eighty HCC patients, 80 liver cirrhosis patients (LC), 80 patients with hepatitis B virus (HBV) infection, and 80 healthy controls (HC) were enrolled. sAxl levels were measured by an enzyme-linked immunosorbent assay, serum AFP levels were measured by an electrochemiluminescence immunoassay. Receiver operating characteristic (ROC) curves were used to evaluate diagnostic performances. Results The results show that levels of sAxl were high expression in patients with HCC (p < 0.05), varied with disease state as follows: HCC > LC > HC > HBV. Logistic regression and ROC curve analysis identified the optimal cut-off for sAxl in differentiating all HCC and non-HCC patients was 1,202 pg/mL (area under the receiver operating characteristic [AUC], 0.888; 95% confidence interval [CI], 0.852 to 0.924) with sensitivity 95.0%, specificity 73.3%. Furthermore, differential diagnosis of early HCC with non-HCC patients for sAxl showed the optimal cut-off was 1,202 pg/mL (AUC, 0.881; 95% CI, 0.831 to 0.931; sensitivity, 94.1%; specificity, 73.3%). Among AFP-negative HCC patients with non-HCC patients, the cut-off was 1,301 pg/mL (AUC, 0.898; 95% CI, 0.854 to 0.942) with a sensitivity of 84.6%, a specificity of 76.3%. The optimal cut-off for sAxl in differentiating all HCC and chronic liver disease patients was 1,243 pg/mL (AUC, 0.840; 95% CI, 0.791 to 0.888) with sensitivity 93.8%, specificity 61.9%. The combination of AFP and sAxl increased diagnostic value for HCC. Conclusion sAxl outperforms AFP in detecting HCC, especially in early HCC and in AFP-negative HCC. Combination sAxl with AFP improved the specificity for early HCC diagnosis. In summary, sAxl is a candidate serum marker for diagnosing HCC.
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