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第四届全国信息检索与内容安全学术会议

作者： Yuejie Zhang~(1,+) Hui Yang~1 Tao Zhang~2 ~1 School of Computer Science,Fudan University,Shanghai 200433,China ~2 School of Information Management & Engineering,Shanghai University of Finance & Economics,Shanghai 200433,China

Chinese new words bring more challenges into Word Segmentation and difficulties for Part-of-Speech (pos)*** paper proposes a SVM-based unified mechanism for Chinese New Word Discovery and pos *** New Word Discovery and pos tagging are defined as a binary classification problem,in which many previous morphological features are *** new features are introduced,such as affix information and context information,as well as some constraints,which reveal the relationships among the new word *** rules are also added to improve the identification *** the experiment,new words are simulated by revising the dictionary of Natural Language Processing *** experimental results show that these features,constraints and rules are all useful for New Word *** F-measure is 64.58%, which is 6.82% higher than the predefined ***,based on the similar processing pattern,the precision of 90.81% for pos tagging of new words can be achieved.

关键词： New Word Discovery pos tagging Support Vector Machine(SVM) feature

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A Semi-Supervised Approach for Aspect Category Detection and Aspect Term Extraction from Opinionated Text

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Computers, Materials & Continua 2023年第10期77卷 115-137页

作者： Bishrul Haq Sher Muhammad Daudpota Ali Shariq Imran Zenun Kastrati Waheed Noor Department of Computer Science Sukkur IBA UniversitySukkur65200Pakistan Department of Computer Science Norwegian University of Science and Technology(NTNU)Gjøvik2815Norway Department of Informatics Linnaeus UniversityVäxjö35195Sweden Department of Computer Science&IT University of BalochistanQuetta87300Pakistan

The Internet has become one of the significant sources for sharing information and expressing users’opinions about products and their interests with the associated *** is essential to learn about product reviews;however,to react to such reviews,extracting aspects of the entity to which these reviews belong is equally ***-based Sentiment Analysis(ABSA)refers to aspects extracted from an opinionated *** literature proposes different approaches for ABSA;however,most research is focused on supervised approaches,which require labeled datasets with manual sentiment polarity labeling and aspect *** study proposes a semisupervised approach with minimal human supervision to extract aspect terms by detecting the aspect ***,the study deals with two main sub-tasks in ABSA,named Aspect Category Detection(ACD)and Aspect Term Extraction(ATE).In the first sub-task,aspects categories are extracted using topic modeling and filtered by an oracle further,and it is fed to zero-shot learning as the prompts and the augmented *** predicted categories are the input to find similar phrases curated with extracting meaningful phrases(e.g.,Nouns,Proper Nouns,NER(Named Entity Recognition)entities)to detect the aspect *** study sets a baseline accuracy for two main sub-tasks in ABSA on the Multi-Aspect Multi-Sentiment(MAMS)dataset along with SemEval-2014 Task 4 subtask 1 to show that the proposed approach helps detect aspect terms via aspect categories.

关键词： Natural language processing sentiment analysis aspect-based sentiment analysis topic-modeling pos tagging zero-shot learning

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Unified Framework of Performing Chinese Word Segmentation and Part-of-Speech tagging

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China Communications 2012年第3期9卷 1-9页

作者： Zhang Kaixu Sun Maosong Tsinghua Univ State Key Lab Intelligent Technol & Syst Dept Comp Sci & Technol Beijing 100084 Peoples R China

The paper proposes a unified framework to combine the advantages of the fast one-at-a-time approach and the high-performance all-at-once approach to perform Chinese Word Segmentation(CWS) and Part-of-Speech(pos) *** this framework,the input of the pos tagger is a candidate set of several CWS results provided by the CWS *** widely used one-at-a-time approach and all-at-once approach are two extreme cases of the proposed candidate-based *** on Penn Chinese Treebank 5 and Tsinghua Chinese Treebank show that the generalized candidate-based approach outperforms one-at-a-time approach and even the all-at-once *** candidate-based approach is also faster than the time-consuming all-at-once *** authors compare three different methods based on sentence,words and character-intervals to generate the candidate *** turns out that the word-based method has the best performance.

关键词： natural language processing Chineseword segmentation pos tagging candidate wordlattice

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