463 research outputs found

    Radical-Enhanced Chinese Character Embedding

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    We present a method to leverage radical for learning Chinese character embedding. Radical is a semantic and phonetic component of Chinese character. It plays an important role as characters with the same radical usually have similar semantic meaning and grammatical usage. However, existing Chinese processing algorithms typically regard word or character as the basic unit but ignore the crucial radical information. In this paper, we fill this gap by leveraging radical for learning continuous representation of Chinese character. We develop a dedicated neural architecture to effectively learn character embedding and apply it on Chinese character similarity judgement and Chinese word segmentation. Experiment results show that our radical-enhanced method outperforms existing embedding learning algorithms on both tasks.Comment: 8 pages, 4 figure

    Joint event extraction based on hierarchical event schemas from framenet

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    Event extraction is useful for many practical applications, such as news summarization and information retrieval. However, the popular automatic context extraction (ACE) event extraction program only defines very limited and coarse event schemas, which may not be suitable for practical applications. FrameNet is a linguistic corpus that defines complete semantic frames and frame-to-frame relations. As frames in FrameNet share highly similar structures with event schemas in ACE and many frames actually express events, we propose to redefine the event schemas based on FrameNet. Specifically, we extract frames expressing event information from FrameNet and leverage the frame-to-frame relations to build a hierarchy of event schemas that are more fine-grained and have much wider coverage than ACE. Based on the new event schemas, we propose a joint event extraction approach that leverages the hierarchical structure of event schemas and frame-to-frame relations in FrameNet. The extensive experiments have verified the advantages of our hierarchical event schemas and the effectiveness of our event extraction model. We further apply the results of our event extraction model on news summarization. The results show that the summarization approach based on our event extraction model achieves significant better performance than several state-of-the-art summarization approaches, which also demonstrates that the hierarchical event schemas and event extraction model are promising to be used in the practical applications

    Design and implementation of an RFID-based customer shopping behavior mining system

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    Shopping behavior data is of great importance in understanding the effectiveness of marketing and merchandising campaigns. Online clothing stores are capable of capturing customer shopping behavior by analyzing the click streams and customer shopping carts. Retailers with physical clothing stores, however, still lack effective methods to comprehensively identify shopping behaviors. In this paper, we show that backscatter signals of passive RFID tags can be exploited to detect and record how customers browse stores, which garments they pay attention to, and which garments they usually pair up. The intuition is that the phase readings of tags attached to items will demonstrate distinct yet stable patterns in a time-series when customers look at, pick out, or turn over desired items. We design ShopMiner, a framework that harnesses these unique spatial-temporal correlations of time-series phase readings to detect comprehensive shopping behaviors. We have implemented a prototype of ShopMiner with a COTS RFID reader and four antennas, and tested its effectiveness in two typical indoor environments. Empirical studies from two-week shopping-like data show that ShopMiner is able to identify customer shopping behaviors with high accuracy and low overhead, and is robust to interference.Department of Computing2016-2017 > Academic research: refereed > Publication in refereed journalbcr

    Expert consensus on resection of chest wall tumors and chest wall reconstruction

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    Chest wall tumors are a relatively uncommon disease in clinical practice. Most of the published studies about chest wall tumors are usually single-center retrospective studies, involving few patients. Therefore, evidences regarding clinical conclusions about chest wall tumors are lacking, and some controversial issues have still to be agreed upon. In January 2019, 73 experts in thoracic surgery, plastic surgery, science, and engineering jointly released the Chinese Expert Consensus on Chest Wall Tumor Resection and Chest Wall Reconstruction (2018 edition). After that, numerous experts put forward new perspectives on some academic issues in this version of the consensus, pointing out the necessity to further discuss the points of contention. Thus, we conducted a survey through the administration of a questionnaire among 85 experts in the world. Consensus has been reached on some major points as follows. (I) Wide excision should be performed for desmoid tumor (DT) of chest wall. After excluding the distant metastasis by multi-disciplinary team, solitary sternal plasmacytoma can be treated with extensive resection and adjuvant radiotherapy. (II) Wide excision with above 2 cm margin distance should be attempted to obtain R0 resection margin for chest wall tumor unless the tumor involves vital organs or structures, including the great vessels, heart, trachea, joints, and spine. (III) For patients with chest wall tumors undergoing unplanned excision (UE) for the first time, it is necessary to carry out wide excision as soon as possible within 1-3 months following the previous surgery. (IV) Current Tumor Node Metastasis staging criteria (American Joint Committee on Cancer) of bone tumor and soft tissue sarcoma are not suitable for chest wall sarcomas. (V) It is necessary to use rigid implants for chest wall reconstruction once the maximum diameter of the chest wall defect exceeds 5 cm in adults and adolescents. (VI) For non-small cell lung cancer (NSCLC) invading the chest wall, wide excision with neoadjuvant and/or adjuvant therapy are recommended for patients with stage T34_{3-4}N01_{0-1}M0_{0}. As clear guidelines are lacking, these consensus statements on controversial issues on chest wall tumors and resection could possibly serve as further guidance in clinical practice during the upcoming years
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