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A place name is a textual identification of a specific spatial location by people and is an important carrier of geographical information. The recognition of Chinese place names is of great importance in information retrieval and event extraction. The traditional approach is to transform the recognition of Chinese place names into a sequential annotation problem, with commonly used classification models such as support vector machines and conditional random fields. In this paper, Chinese address recognition is converted into a sequential annotation task, and a multi-feature fusion approach to Chinese address recognition is proposed. A deep learning network architecture model based on the fusion of character, word, and address features is constructed to convert characters, words, and their features into vector representations; finally, the sequential annotation of sentences is performed by CRF to achieve the recognition and extraction of address information. On the autonomously constructed dataset, the proposed method MFBL (Multi-Feature-BiLSTM) improves in accuracy by 4 to 10 percentage points compared to other methods, demonstrating that the MFBL model has better performance in the address recognition task.

Address recognition, as one of the important scenarios of natural language processing in big data applications, is an important and extremely practical technical means. Currently, the evolution of big data applications is being actively promoted, and more and more people are using big data technology to empower power address recognition. Address information in many data assets is the core area of connected devices, and the analysis and mining of core algorithms has extremely high value. This paper first analyzes the application scenarios involved in the common address information of electric power, and formulates the extraction and matching method according to the key points of the core application scenarios and the address recognition requirements; then, based on the data samples, the accuracy and calculation speed of the address recognition method are studied, and the Algorithms are analyzed and compared. Practicality; finally summarize the algorithm, and look forward to ways to improve the algorithm in the future.

Collinear acoustooptic (AO) switches are investigated for use in label recognition system in photonic routing systems. The optical label discussed in this paper uses optical codes which are encoded in the time domain. Short optical pulse trains representing the codes are processed with integrated AO devices. Proposed device configurations for label recognition are described with the basic operation mechanism. A numerical example for the code recognition is also presented. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 159(3): 48–55, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20453 [ABSTRACT FROM AUTHOR]

The routing functionality by all-optically interconnecting semiconductor-based all-optical logic gates and flip-flops is demonstrated in the frame of an all-optical label swapping (AOLS) network. We experimentally show that the output of the all-optical 2-bit correlator is capable of toggling the states of the integrated flip-flop every 2.5 ns via an adaptation stage. High extinction ratios are obtained at the output of the flip-flop, which can be used to feed a high-speed wavelength converter to complete the routing functionality of the AOLS node. The potential integration of these semiconductor optical amplifier integrated Mach-Zehnder interferometer-based devices make the proposed approach a very interesting solution for future packet switched optical networks. [ABSTRACT FROM PUBLISHER]

In this letter, we demonstrate that all-optical network subsystems, offering intelligence in the optical layer, can be constructed by functional integration of integrated all-optical logic gates and flip-flops. In this context, we show 10-Gb/s all-optical 2-bit label address recognition by interconnecting two optical gates that perform xor operation on incoming optical labels. We also demonstrate 40-Gb/s all-optical wavelength-switching through an optically controlled wavelength converter, consisting of an integrated flip-flop prototype device driven by an integrated optical gate. The system-level advantages of these all-optical subsystems combined with their realization with compact integrated devices, suggest that they are strong candidates for future packet/label switched optical networks [ABSTRACT FROM PUBLISHER]