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2017 2nd International Conference on Computer Engineering,information Science and Internet Technology(CII 2017)

作者： SHUMIN SHI MENG ZHAO JUN GUAN HEYAN HUANG School of Computer Science and Technology Beijing Institute of Technology Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications

With the development of social network,group emotion analysis on social media such as Facebook,Twitter and Weibo becomes a new trend in recent *** different methods have been proposed for group emotion analysis,including traditional methods like SVM and NB and deep learning methods like RNN and *** paper proposes a CNN model with *** first analyze the characteristic of weibos to collect features including basic features,user-based features and content-based *** introduce these features to our CNN model to analyze emotions for Weibo events,which has been proved in experiment that it is effective to get the accurate sentiment of *** crawl 5,319,687 weibos about 724 events from Sina Weibo and apply several feature matrices to classify them to 4 *** use the new model to analyze 4 kinds of events to get the group *** results suggest that the classification we suggested can capture the emotions within different event group.

关键词： Social media Sentiment analysis Group emotion Deep learning Convolutional neural networks

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Unsupervised Style Control for Image Captioning

Unsupervised Style Control for Image Captioning

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作者： Junyu Tian Zhikun Yang Shumin Shi School of Computer Science and Technology Beijing Institute of Technology Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications

We propose a novel unsupervised image captioning *** captioning involves two fields of deep learning,natural language processing and computer *** excessive pursuit of model evaluation results makes the caption style generated by the model too monotonous,which is difficult to meet people's demands for vivid and stylized image ***,we propose an image captioning model that combines text style transfer and image emotion recognition methods,with which the model can better understand images and generate controllable stylized *** proposed method can automatically judge the emotion contained in the image through the image emotion recognition module,better understand the image content,and control the description through the text style transfer method,thereby generating captions that meet people's *** our knowledge,this is the first work to use both image emotion recognition and text style control.

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Utilizing Crowdsourcing for the Construction of Chinese-Mongolian Speech Corpus with Evaluation Mechanism

Utilizing Crowdsourcing for the Construction of Chinese-Mong...

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The Third International Conference of Pioneering Computer Scientists, Engineers and Educators,ICPCSEE 2017(originally ICYCSEE)

作者： Rihai Su Shumin Shi Meng Zhao Heyan Huang School of Computer Sciences and Technology Beijing Institute of Technology Beijing Engineering Research Centre of High Volume Language Information Processing and Cloud Computing Applications

Crowdsourcing has been used recently as an alternative to traditional costly annotation by many natural language processing groups. In this paper, we explore the use of Wechat Official Account Platform(WOAP) in order to build a speech corpus and to assess the feasibility of using WOAP followers(also known as contributors) to assemble speech corpus of Mongolian. A Mongolian language qualification test was used to filter out potential non-qualified participants. We gathered natural speech recordings in our daily life, and constructed a ChineseMongolian Speech Corpus(CMSC) of 31472 utterances from 296 native speakers who are fluent in Mongolian, totalling 30.8 h of speech. Then,an evaluation experiment was performed, in where the contributors were asked to choose a correct sentence from a multiple choice list to ensure the high-quality of corpus. The results obtained so far showed that crowdsourcing for constructing CMSC with an evaluation mechanism could be more effective than traditional experiments requiring expertise.

关键词： Crowdsourcing Chinese-Mongolian corpus Speech corpus WOAP Evaluation mechanism

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

arXiv

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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

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Effective Fuzzing Based on Dynamic Taint Analysis

Effective Fuzzing Based on Dynamic Taint Analysis

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International Conference on Computational Intelligence and Security

作者： Guangcheng Liang Lejian Liao Xin Xu Jianguang Du Guoqiang Li Henglong Zhao Beijing Engineering Research Center of High Volume Language Information Processing & Cloud Computing Applications Beijing Institute of Technology Beijing China DISECC Beijing China

In this paper we present a new vulnerability-targeted black box fuzzing approach to effectively detect errors in the program. Unlike the standard fuzzing techniques that randomly change bytes of the input file, our approach remarkably reduces the fuzzing range by utilizing an efficient dynamic taint analysis technique. It locates the regions of seed files that affect the values used at the hazardous points. Thus it enables to pay more attention to deep errors in the core of the program. Because our approach is directly targeted to the specific potential vulnerabilities, most of the detected errors are with vulnerability signatures. Besides, this approach does not need the information of the input file format in advance. So it is especially appropriate for testing applications with complex and highly structured input file formats. We design and implement a prototype, Taint Fuzz, to realize this approach. The experiments demonstrate that Taint Fuzz can effectively expose more errors with much lower time cost and much smaller number of input samples compared with the standard fuzzer.

关键词： Software Performance analysis Standards Security Instruments Testing Memory management

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Named entity recognition based on bilingual co-training

Named entity recognition based on bilingual co-training

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14th Workshop on Chinese Lexical Semantics, CLSW 2013

作者： Li, Yegang Huang, Heyan Zhao, Xingjian Shi, Shumin School of Computer Science and Technology Beijing Institute of Technology Beijing China Beijing Eng. Applic. Res. Center of High Volume Language Information Processing and Cloud Computing Beijing Institute of Technology Beijing China Department of Computer Science and Technology Shandong University of Technology Zibo Shandong China

ISBN: (纸本)9783642451843

Named entity recognition (NER) is a very important task in natural language processing (NLP). In this paper we present a semi-supervised approach to extract bilingual named entity, starting from a bilingual corpus where the named entities are extracted independently for each language. Then a bilingual co-training algorithm is used to improve the named entity annotation quality, and iterative process is applied to extract named entity pairs with higher bilingual conformity ratio. This leads to a significant improvement of the monolingual named entity annotation quality for both languages. Experimental result shows that the annotation quality of Chinese NE is improved from 87.17 to 88.28, and improved 80.37 to 81.76 of English NE in F-measure. © 2013 Springer-Verlag.

关键词： Iterative methods

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A Novel Multimodal Sentiment Analysis Model Based on Gated Fusion and Multi-Task Learning

A Novel Multimodal Sentiment Analysis Model Based on Gated F...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Xin Sun Xiangyu Ren Xiaohao Xie School of Computer Science and Technology Beijing Institute of Technology China Beijing Engineering Applications Research Center on High Volume Language Information Processing and Cloud Computing

Sentiment analysis is an important research area in Natural language processing (NLP). With the explosion of multimodal data, Multimodal Sentiment Analysis (MSA) attracts more and more attention in recent years. How to Effectively harnessing the interplay between diverse modalities is paramount to achieving comprehensive fusion of MSA. However, current research predominantly emphasizes modality interaction, while overlooking unimodal information, thus neglecting the inherent disparities between modalities. To address these issues, we propose a novel model for multimodal sentiment analysis based on gated fusion and multi-task learning. The model adopts multi-task learning to concurrently address both multimodal and unimodal sentiment analysis tasks. Specifically, for the multimodal task, we leverage cross-modal Transformers with gating mechanisms to facilitate modality fusion. Subsequently, the fused representations are harnessed to generate sentiment labels for the unimodal tasks. Experiments on the CMU-MOSI and CMU-MOSEI datasets demonstrate that our model outperforms the existing methods and achieves the state-of-the art performance.

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Microblog Keyphrase Extraction Based on Similarity Features

Microblog Keyphrase Extraction Based on Similarity Features

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2013 International Conference on Advanced Computer Science and Electronics information(ICACSEI 2013)

作者： Lizi Liao Heyan Huang Beijing Engineering Applications Research Center of High Volume Language Information Processing and Cloud Computing (BIT) School of Computer Science and Technology Beijing Institute of Technology

This paper proposes to extract keyphrases from microblog based on similarity features. We analyze a large number of microblogs and find an interesting phenomenon that people use various nugget phrases to express the same factoid while many of these nugget phrases show similarity relationships. We propose a similarity features based context-sensitive topical PageRank method for keyphrase ranking. We evaluate our proposed methods on a large microblog dataset. Experiments show that our system is very effective for keyphrase extraction.

关键词： Keyphrase extraction, Similarity features, Graph- based model

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

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

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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

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A hierarchy-based constraint dependency grammar parsing for Chinese

A hierarchy-based constraint dependency grammar parsing for ...

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International Conference on Audio, language and Image processing, ICALIP

作者： Peng Li Lejian Liao Xin Li Beijing Engineering Research Centre of High Volume Language Information Processing & Cloud Computing Applications School of Computer Science Beijing Institute of Technology Beijing China

Constraint Dependency Grammar (CDG) is a well known formalism which represents the grammatical rules as constraints on dependency relations. It reduces the structural ambiguities via constraint-propagation instead of generating individual parse trees as the conventional works. In our previous work, we have successfully adopted CDG in Chinese [5]. In this paper, we tend to further explore the nature of the constraints for Chinese CDG. We propose to develop a schema of three hierarchies for the constraints, namely in-the-phrase, between-the-phrase and between-the-simple-sentence, which is based on a study of constraints in corpus with a prior knowledge. With this proposed schema, we could further diminish the ambiguities caused by the originally defined constraints which is lack of hierarchical grammar information considered, The experiments are conducted and the results support our claims.

关键词： Grammar Syntactics Filtering information processing Educational institutions Semantics Presses

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