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Word sense disambiguation based on rough set

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Journal of Harbin Institute of Technology(New Series) 2002年第2期9卷 201-204页

作者：陈清才王晓龙赵健陈滨王长风 Dept. of Computer Science and Engineering Harbin Institute of Technology Harbin 150001 China ***

A sense feature system (SFS) is first automatically constructed from the text corpora to structurize the textural information. WSD rules are then extracted from SFS according to their certainty factors and are applied to disambiguate the senses of polysemous words. The entropy of a deterministic rough prediction is used to measure the decision quality of a rule set. Finally, the back off rule smoothing method is further designed to improve the performance of a WSD model. In the experiments, a mean rate of correction achieved during experiments for WSD in the case of rule smoothing is 0.92.

关键词： word sense disambiguation rough set sense feature system

Word Sense disambiguation in Information Retrieval

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Intelligent Information Management 2009年第2期1卷 122-127页

作者： Francis de la C. Fernández REYES Exiquio C. Pérez LEYVA Rogelio Lau FERNáNDEZ Instituto Superior Politecnico Jose Antonio Echeverria

The natural language processing has a set of phases that evolves from lexical text analysis to the pragmatic one in which the author’s intentions are shown. The ambiguity problem appears in all of these tasks. Previous works tries to do word sense disambiguation, the process of assign a sense to a word inside a specific context, creating algorithms under a supervised or unsupervised approach, which means that those algorithms use or not an external lexical resource. This paper presents an approximated approach that combines not supervised algorithms by the use of a classifiers set, the result will be a learning algorithm based on unsupervised methods for word sense disambiguation process. It begins with an introduction to word sense disambiguation concepts and then analyzes some unsupervised algorithms in order to extract the best of them, and combines them under a supervised approach making use of some classifiers.

关键词： disambiguation algorithms natural language processing word sense disambiguation

Using Wikipedia as an External Knowledge Source for Supporting Contextual disambiguation

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Journal of Software Engineering and Applications 2012年第12期5卷 175-180页

作者： Shahida Jabeen Xiaoying Gao Peter Andreae School of Engineering and Computer Science Victoria University of Wellington New Zealand

Every term has a meaning but there are terms which have multiple meanings. Identifying the correct meaning of a term in a specific context is the goal of Word Sense disambiguation (WSD) applications. Identifying the correct sense of a term given a limited context is even harder. This research aims at solving the problem of identifying the correct sense of a term given only one term as its context. The main focus of this research is on using Wikipedia as the external knowledge source to decipher the true meaning of each term using a single term as the context. We experimented with the semantically rich Wikipedia senses and hyperlinks for context disambiguation. We also analyzed the effect of sense filtering on context extraction and found it quite effective for contextual disambiguation. Results have shown that disambiguation with filtering works quite well on manually disambiguated dataset with the performance accuracy of 86%.

关键词： Contextual disambiguation Wikipedia Hyperlinks Semantic Relatedness

Adaptive Resonance Theory Based Two-Stage Chinese Name disambiguation

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International Journal of Intelligence Science 2012年第4期2卷 83-88页

作者： Xin Wang Yuanchao Liu Xiaolong Wang Ming Liu Bingquan Liu School of Computer Science and Technology Harbin Institute of Technology Harbin China

It’s common that different individuals share the same name, which makes it time-consuming to search information of a particular individual on the web. Name disambiguation study is necessary to help users find the person of interest more readily. In this paper, we propose an Adaptive Resonance Theory (ART) based two-stage strategy for this problem. We get a first-stage clustering result with ART1 model and then merge similar clusters in the second stage. Our strategy is a mimic process of manual disambiguation and need not to predict the number of clusters, which makes it competent for the disambiguation task. Experimental results show that, in comparison with the agglomerative clustering method, our strategy improves the performance by respectively 0.92% and 5.00% on two kinds of name recognition results.

关键词： Name disambiguation Adaptive Resonance Theory Text Clustering Natural Language Processing

Name disambiguation Method Based on Attribute Match and Link Analysis

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Journal of Software Engineering and Applications 2012年第1期5卷 29-32页

作者： Yu-Feng Yao Changshu Institute of Technology Computer Science and Engineering College

A name disambiguation method is proposed based on attribute match and link analysis applying in the field of insurance. Aiming at the former name disambiguation methods such as text clustering method needs to be considered in a lot of useless words, a new name disambiguation method is advanced. Firstly, the same attribute matching is applied, merging the identity of a successful match, secondly, the link analysis is used, structural analysis of customers network is analyzed, Finally, the same cooperating information is merged. Experiment results show that the proposed method can realize name disambiguation successfully.

关键词： Name disambiguation Data Mining Attribute Match Link Analysis

An Improved Name disambiguation Method Based on Atom Cluster

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Communications and Network 2012年第1期4卷 30-33页

作者： Yu-Feng Yao Computer Science and Engineering College Changshu Institute of Technology Suzhou China

An improved name disambiguation method based on atom cluster. Aiming at the method of character-related properties of similarity based on information extraction depends on the character information, a new name disambiguation method is proposed, and improved k-means algorism for name disambiguation is proposed in this paper. The cluster analysis cluster is introduced to the name disambiguation process. Experiment results show that the proposed method having the high implementation efficiency and can distinguish the different people with the same name.

关键词： Relation Name disambiguation Data Mining Entity

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基于无导词义消歧的语义查询扩展

情报学报 2011年第2期30卷 131-137页

作者：王瑞琴孔繁胜温州大学计算机科学与工程学院温州325035 浙江大学人工智能研究所杭州310027

一个构造良好的查询是信息检索质量的基本保证,语义查询扩展技术解决了传统信息检索系统不能很好理解用户查询意图的问题,在提高检索查全率的同时保证了检索准确率.本文以查询关键字之间的语义关联为切入点,辅以隐式反馈技术获取消歧上... 详细信息

一个构造良好的查询是信息检索质量的基本保证,语义查询扩展技术解决了传统信息检索系统不能很好理解用户查询意图的问题,在提高检索查全率的同时保证了检索准确率.本文以查询关键字之间的语义关联为切入点,辅以隐式反馈技术获取消歧上下文,以WordNet本体库和WordNet Domains扩展库作为消歧数据源,使用基于局部上下文和基于图论的两类无导词义消歧方法进行查询关键字到本体概念的映射,最后基于概念词汇关联完成基于语义的查询扩展.综合WordNet本体库和WordNet Domains扩展库中的各项知识源对查询词义进行判定,保证了词义消歧的精度;采用无导词义消歧实现查询词义的快速判定,保证了信息检索的实时性;根据查询关键词的多寡分别提出两类消歧方法,满足了各种查询需求.

关键词：词义消歧语义查询扩展 Word Sense disambiguation Based Query Expansion WordNet 信息检索系统消歧方法上下文扩展库关键字本体库检索准确率语义关联隐式反馈快速判定检索质量技术解决技术获取基于语义

Label correlation for partial label learning

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Journal of Systems Engineering and Electronics 2022年第5期33卷 1043-1051页

作者： GE Lingchi FANG Min LI Haikun CHEN Bo School of Computer Science and Technology Xidian UniversityXi’an 710071China

Partial label learning aims to learn a multi-class classifier,where each training example corresponds to a set of candidate labels among which only one is *** studies in the label space have only focused on the difference between candidate labels and non-candidate *** far,however,there has been little discussion about the label correlation in the partial label *** paper begins with a research on the label correlation,followed by the establishment of a unified framework that integrates the label correlation,the adaptive graph,and the semantic difference maximization *** work generates fresh insight into the acquisition of the learning information from the label ***,the label correlation is calculated from the candidate label set and is utilized to obtain the similarity of each pair of instances in the label *** that,the labeling confidence for each instance is updated by the smoothness assumption that two instances should be similar outputs in the label space if they are close in the feature *** last,an effective optimization program is utilized to solve the unified *** experiments on artificial and real-world data sets indicate the superiority of our proposed method to state-of-art partial label learning methods.

关键词： pattern recognition partial label learning label correlation disambiguation

A Multi-match Approach to the Author Uncertainty Problem

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Journal of Data and Information Science 2019年第2期4卷 1-18页

作者： Stephen F.Carley Alan L.Porter Jan L.Youtie Search Technology Inc Georgia Institute of Technology Enterprise Innovation Institute Georgia Institute of Technology

Purpose: The ability to identify the scholarship of individual authors is essential for performance evaluation. A number of factors hinder this endeavor. Common and similarly spelled surnames make it difficult to isolate the scholarship of individual authors indexed on large databases. Variations in name spelling of individual scholars further complicates matters. Common family names in scientific powerhouses like China make it problematic to distinguish between authors possessing ubiquitous and/or anglicized surnames(as well as the same or similar first names). The assignment of unique author identifiers provides a major step toward resolving these difficulties. We maintain, however, that in and of themselves, author identifiers are not sufficient to fully address the author uncertainty problem. In this study we build on the author identifier approach by considering commonalities in fielded data between authors containing the same surname and first initial of their first name. We illustrate our approach using three case ***/methodology/approach: The approach we advance in this study is based on commonalities among fielded data in search results. We cast a broad initial net—i.e., a Web of Science(WOS) search for a given author's last name, followed by a comma, followed by the first initial of his or her first name(e.g., a search for ‘John Doe' would assume the form: ‘Doe, J'). Results for this search typically contain all of the scholarship legitimately belonging to this author in the given database(i.e., all of his or her true positives), along with a large amount of noise, or scholarship not belonging to this author(i.e., a large number of false positives). From this corpus we proceed to iteratively weed out false positives and retain true positives. Author identifiers provide a good starting point—e.g., if ‘Doe, J' and ‘Doe, John' share the same author identifier, this would be sufficient for us to conclude these are one and the same individual. We fin

关键词： Name disambiguation Author identifiers Multi-match approach