Recommendation algorithm is the most core and key point in recommender systems, and plays a decisive role in type and performance evaluation. At present collaborative filtering recommendation not only is the most widely useful and successful recommend technology, but also is a promotion for the study of the whole recommender systems. The research on the recommender systems is coming into a focus and critical problem at home and abroad. Firstly, the latest development and research in the collaborative filtering recommendation algorithm are introduced. Secondly, the primary idea and difficulties faced with the algorithm are explained in detail. Some classical solutions are used to deal with the problems such as data sparseness, cold start and augmentability. Thirdly, the particular evaluation method of the algorithm is put forward and the developments of collaborative filtering algorithm are prospected.
Fully automatic methods that extract structured data from the Web have been studied extensively. The existing methods suffice for simple extraction, but they often fail to handle more complicated Web pages. This paper introduces a method based on tag path clustering to extract structured data. The method gets complete tag path collection by parsing the DOM tree of the Web document. Clustering of tag paths is performed based on introduced similarity measure and the data area can be targeted, then taking advantage of features of tag position, we can separate and filter record, finally complete data extraction. Experiments show this method achieves higher accuracy than previous methods.
Chemical sensors is gaining long-standing interests due to their applications in many areas such as bacterial and virus detection, medical diagnostics, drug development, food safety and environmental control. Among the existing chemical sensors, optical planar sensors show promising and attempt to beat their commercialized competitors because of their robustness, lable-free detection mechanism, mature complementary metal oxide semiconductor (coms) fabrication technology and naturally low cost. Silicon nitride microring resonators were demonstrated as chemical sensors. Using the technique of coms technology, the microring devices were fabricated with 200 µm in radius. Performance of the devices was measured, which showed the quality factor (q) was up to 25,000. Sensitivity of 108.9336 nm per reflective index unit (nm/riu) and detection limit of 1.836×10-4 riu were demonstrated by using various concentrations of ethanol solution as analytes.
There are so many Deep Webs in Internet, which contains a large amount of valuable data, This paper proposes a Deep Web data extraction and service system based on the principle of cloud technology. We adopt a kind of multi-node parallel computing system structure and design a task scheduling algorithm in the data extraction process, in above foundation, balance the task load of among nodes to accomplish data extraction rapidly; The experimental results show that cloud parallel computing and dispersed network resources are used to extract data in Deep Web system is valid and improves the data extraction efficiency of Deep Web and service quality.
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