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Hierarchical Domain Assignment BaseC on Word-Gloss

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China Communications 2012年第3期9卷 19-27页

作者：朱朝勇黄河燕史树敏 School of Computer Science and Technology University of Science and Technology of China School of Computer Science and Technology Beijing Institute of Technology Beijing Engineering Research Center of High Volume Language Information Processing & Cloud Computing Applications Beijing Institute of Technology

This paper proposes a hierarchical word domain assignment algorithm to automatically build domain dictionaries from Machine-Readable Dictionary(MRD).The process for word domain assignment can be divided into three steps:1) Hierarchical structure constructing;2) Classifier training;3) Word domain *** with the traditional methods,the hierarchical word domain assignment algorithm enhances the accuracy of word domain assignment while reducing human efforts on collecting *** on WordNet 2.0 show that 62.53% of the first domain labels are matched with the WordNet Domains 3.0 by using gloss-based word domain assignment,and the performance can be further improved by utilizing the hierarchical relationships among the domain sets.

关键词： natural language processing domaindictionary hierarchical classification domain as-sigrmaent WordNet MRD

A privacy-preserving traffic monitoring scheme via vehicular crowdsourcing

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arXiv 2019年

作者： Zhang, Chuan Zhu, Liehuang Xu, Chang Du, Xiaojiang Guizani, Mohsen Beijing Eng. Res. Center of Massive Language Information Processing and Cloud Computing Application School of Computer Science and Technology Beijing Institute of Technology Beijing China Department of Computer and Information Sciences Temple University Philadelphia United States College of Engineering Qatar University

The explosive growth of vehicle amount has given rise to a series of traffic problems, such as traffic congestion, road safety, and fuel waste. Collecting vehicles' speed information is an effective way to monitor the traffic condition and avoid vehicles being congested, which however may bring threats to vehicles' location and trajectory privacy. Motivated by the fact that traffic monitoring does not need to know each individual vehicle's speed and the average speed would be sufficient, we propose a privacy-preserving traffic monitoring (PPTM) scheme to aggregate vehicles' speeds at different locations. In PPTM, the roadside unit (RSU) collects vehicles' speed information at multiple road segments, and further cooperates with a service provider to calculate the average speed information for every road segment. To preserve vehicles' privacy, both homomorphic Paillier cryptosystem and super-increasing sequence are adopted. A comprehensive security analysis indicates that the proposed PPTM can preserve vehicles' identities, speeds, locations, and trajectories privacy from being disclosed. In addition, extensive simulations are conducted to validate the effectiveness and efficiency of the proposed PPTM scheme. Copyright © 2019, The Authors. All rights reserved.

关键词： Speed

A parallel cross-language retrieval system for patent documents

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A parallel cross-language retrieval system for patent docume...

IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Xin Shen Heyan Huang Lingzhi Li Yonggang Huang Beijing Engineering Research Center of High Volume Language Information Processing & Cloud Computing Application Beijing Institute of Technology Beijing China Overhaul Branch Beijing Electric Power Company Beijing China

ISBN: (纸本)9781479983544

In order to help people obtain useful information from patent documents in different languages. This paper proposes a cross-language retrieval system to search Chinese and English patent documents simultaneously. This system consists of query translation module, document retrieval module and user interaction module. Query translation module is used to translate query based on bilingual dictionaries. Document retrieval module consists of monolingual retrieval system using standard vector space model. In order to retrieve in highly parallel, we use the MapReduce model to calculate the similarity. User interaction module provides users with interactive mechanism used to improve the retrieval accuracy in the system. It contains two parts: the second translation and relevance feedback. The experimental results show that our system has good performance.

关键词： Patents Dictionaries Context Data processing Accuracy Machine learning algorithms

SDN controllers: Benchmarking & performance evaluation

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arXiv 2019年

作者： Zhu, Liehuang Karim, Md Monjurul Sharif, Kashif Li, Fan Du, Xiaojiang Guizani, Mohsen Beijing Engineering Research Center for Massive Language Information Processing & Cloud Computing Application School of Computer Science and Technology Beijing Institute of Technology Beijing China Department of Computer and Information Sciences Temple University Philadelphia United States Department of Electrical and Computer Engineering University of Idaho MoscowID United States

Software Defined Networks offer flexible and intelligent network operations by splitting a traditional network into a centralized control plane and a programmable data plane. The intelligent control plane is responsible for providing flow paths to switches and optimizes network performance. The controller in the control plane is the fundamental element used for all operations of data plane management. Hence, the performance and capabilities of the controller itself are extremely important. Furthermore, the tools used to benchmark their performance must be accurate and effective in measuring different evaluation parameters. There are dozens of controller proposals available in existing literature. However, there is no quantitative comparative analysis for them. In this article, we present a comprehensive qualitative comparison of different SDN controllers, along with a quantitative analysis of their performance in different network scenarios. More specifically, we categorize and classify 34 controllers based on their capabilities, and present a qualitative comparison of their properties. We also discuss in-depth capabilities of benchmarking tools used for SDN controllers, along with best practices for quantitative controller evaluation. This work uses three benchmarking tools to compare nine controllers against multiple criteria. Finally, we discuss detailed research findings on the performance, benchmarking criteria, and evaluation testbeds for SDN controllers. Copyright © 2019, The Authors. All rights reserved.

关键词： Benchmarking

PSST: A Benchmark for Evaluation-driven Text Public-Speaking Style Transfer

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arXiv 2023年

作者： Sun, Huashan Wu, Yixiao Ye, Yuhao Yang, Yizhe Li, Yinghao Li, Jiawei Gao, Yang School of Computer Science and Technology Beijing Institute of Technology Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications China

language style is necessary for AI systems to understand and generate diverse human language accurately. However, previous text style transfer primarily focused on sentence-level data-driven approaches, limiting exploration of potential problems in large language models (LLMs) and the ability to meet complex application needs. To overcome these limitations, we introduce a novel task called Public-Speaking Style Transfer (PSST), which aims to simulate humans to transform passage-level, official texts into a public-speaking style. Grounded in the analysis of real-world data from a linguistic perspective, we decompose public-speaking style into key sub-styles to pose challenges and quantify the style modeling capability of LLMs. For such intricate text style transfer, we further propose a fine-grained evaluation framework to analyze the characteristics and identify the problems of stylized texts. Comprehensive experiments suggest that current LLMs struggle to generate public speaking texts that align with human preferences, primarily due to excessive stylization and loss of semantic information Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

PRIF: A Privacy-Preserving Interest-Based Forwarding Scheme for Social Internet of Vehicles Liehuang Zhu, Chuan Zhang, Chang Xu, Rixin Xu, Kashif Sharif are with

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arXiv 2018年

作者： Zhu, Liehuang Zhang, Chuan Xu, Chang Du, Xiaojiang Xu, Rixin Sharif, Kashif Guizani, Mohsen Beijing Eng. Res. Center of Massive Language Information Processing and Cloud Computing Application Beijing Institute of Technology School of Computer Science and Technology Beijing China Department of Computer and Information Sciences Temple University Philadelphia United States Department of Electrical and Computer Engineering University of Idaho Moscow Idaho United States

Recent advances in Socially Aware Networks (SANs) have allowed its use in many domains, out of which social Internet of vehicles (SIOV) is of prime importance. SANs can provide a promising routing and forwarding paradigm for SIOV by using interest-based communication. Though able to improve the forwarding performance, existing interest-based schemes fail to consider the important issue of protecting users' interest information. In this paper, we propose a PRivacy-preserving Interest-based Forwarding scheme (PRIF) for SIOV, which not only protects the interest information, but also improves the forwarding performance. We propose a privacy-preserving authentication protocol to recognize communities among mobile nodes. During data routing and forwarding, a node can know others' interests only if they are affiliated with the same community. Moreover, to improve forwarding performance, a new metric community energy is introduced to indicate vehicular social proximity. Community energy is generated when two nodes encounter one another and information is shared among them. PRIF considers this energy metric to select forwarders towards the destination node or the destination community. Security analysis indicates PRIF can protect nodes' interest information. In addition, extensive simulations have been conducted to demonstrate that PRIF outperforms the existing algorithms including the BEEINFO, Epidemic, and PRoPHET. Copyright © 2018, The Authors. All rights reserved.

关键词： Vehicles

PPLS: A privacy-preserving location-sharing scheme in vehicular social networks

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arXiv 2018年

作者： Xu, Chang Xie, Xuan Zhu, Liehuang Sharif, Kashif Zhang, Chuan Du, Xiaojiang Guizani, Mohsen Beijing Eng. Res. Center of Massive Language Information Processing and Cloud Computing Application Beijing Institute of Technology School of Computer Science and Technology Beijing China Department of Computer and Information Sciences Temple University Philadelphia United States Department of Electrical and Computer Engineering University of Idaho MoscowID United States

The recent proliferation of mobile computing has given rise to vehicular so-cial networks (VSNs) which use the Internet of Vehicles and social networks as the main design elements. As one of the most critical components in VSNs, location sharing plays an important role in helping vehicles share information and strengthen their social bonds. This, however, may compromise vehicles' privacy, including location information and social relationship details. Some solutions have been proposed to address these challenges. However, none of them considers privacy of inter-user threshold distance, which e_ectively can be used to identify vehicles, their friends, and location information, by mali-cious or undesired elements of the system. In order to overcome this limitation, we propose a secure distance comparison protocol. Furthermore, we present a privacy-preserving location-sharing scheme in VSNs, namely PPLS, which al-lows vehicles to build more complex access control policies. The safety of our scheme is validated by the security analysis, and experimental results demon-strate the eficiency of PPLS scheme. Copyright © 2018, The Authors. All rights reserved.

关键词： Vehicles

QACtools: A Quality Assessment and Quality Control Tool for Next-Generation Sequencing Data

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QACtools: A Quality Assessment and Quality Control Tool for ...

2015年中国智能自动化学术会议

作者： Dandan Song Ning Li Lejian Liao Beijing Lab of Intelligent Information Technology School of Computer Science and Technology Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing Institute of Technology

In recent years, next-generation sequencing technologies have been widely used, and are rapidly changing the landscape of genetics with unimaginable speed. However, the preliminary quality control regulations including trimming adaptor sequences, quality statistics, and depth and coverage statistics need to be applied to raw reads before further analysis. QACtools implements various utilities for processing raw reads in the FASTQ format and alignments in the BAM *** analyzes some relevant properties of next-generation sequencing data such as average read length, base quality scores, and so on. Additionally, to our knowledge,none of the other tools support depth and coverage statistic that have been provided in our tool for analysis of large DNA sequencing data. It is crucial for overcoming errors in base calling and assembly. We suppose tool is useful for the quality control of NGS data to perform further analysis. This software is an open source application freely available at https://***/projects/qactools/.

关键词： NGS data analysis Quality control FASTQ format BAM format

Prediction or comparison: Toward interpretable qualitative reasoning

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arXiv 2021年

作者： Ren, Mucheng Huang, Heyan Gao, Yang School of Computer Science and Technology Beijing Institute of Technology Beijing China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing China

Qualitative relationships illustrate how changing one property (e.g., moving velocity) affects another (e.g., kinetic energy) and constitutes a considerable portion of textual knowledge. Current approaches use either semantic parsers to transform natural language inputs into logical expressions or a "black-box" model to solve them in one step. The former has a limited application range, while the latter lacks interpretability. In this work, we categorize qualitative reasoning tasks into two types: prediction and comparison. In particular, we adopt neural network modules trained in an end-to-end manner to simulate the two reasoning processes. Experiments on two qualitative reasoning question answering datasets, QuaRTz and QuaRel, show our methods' effectiveness and generalization capability, and the intermediate outputs provided by the modules make the reasoning process interpretable. Copyright © 2021, The Authors. All rights reserved.

关键词： Kinetics