International Conference on Language, Data, and Knowledge最新文献_第5页

Exploiting Background Knowledge for Argumentative Relation Classification 利用背景知识进行论证关系分类

International Conference on Language, Data, and Knowledge Pub Date : 1900-01-01 DOI: 10.4230/OASICS.LDK.2019.8

J. Kobbe, J. Opitz, Maria Becker, Ioana Hulpus, H. Stuckenschmidt, A. Frank

{"title":"Exploiting Background Knowledge for Argumentative Relation Classification","authors":"J. Kobbe, J. Opitz, Maria Becker, Ioana Hulpus, H. Stuckenschmidt, A. Frank","doi":"10.4230/OASICS.LDK.2019.8","DOIUrl":"https://doi.org/10.4230/OASICS.LDK.2019.8","url":null,"abstract":"Argumentative relation classification is the task of determining the type of relation (e.g., support or attack) that holds between two argument units. Current state-of-the-art models primarily exploit surface-linguistic features including discourse markers, modals or adverbials to classify argumentative relations. However, a system that performs argument analysis using mainly rhetorical features can be easily fooled by the stylistic presentation of the argument as opposed to its content, in cases where a weak argument is concealed by strong rhetorical means. This paper explores the difficulties and the potential effectiveness of knowledge-enhanced argument analysis, with the aim of advancing the state-of-the-art in argument analysis towards a deeper, knowledge-based understanding and representation of arguments. We propose an argumentative relation classification system that employs linguistic as well as knowledge-based features, and investigate the effects of injecting background knowledge into a neural baseline model for argumentative relation classification. Starting from a Siamese neural network that classifies pairs of argument units into support vs. attack relations, we extend this system with a set of features that encode a variety of features extracted from two complementary background knowledge resources: ConceptNet and DBpedia. We evaluate our systems on three different datasets and show that the inclusion of background knowledge can improve the classification performance by considerable margins. Thus, our work offers a first step towards effective, knowledge-rich argument analysis.","PeriodicalId":377119,"journal":{"name":"International Conference on Language, Data, and Knowledge","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126069456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

Calculating Argument Diversity in Online Threads 在线线程中参数多样性的计算

International Conference on Language, Data, and Knowledge Pub Date : 1900-01-01 DOI: 10.4230/OASIcs.LDK.2021.39

Cedric Waterschoot, A. V. D. Bosch, E. Hemel

引用次数: 0

Ligt: An LLOD-Native Vocabulary for Representing Interlinear Glossed Text as RDF light:一种llod原生词汇表，用于将行间有光泽文本表示为RDF

International Conference on Language, Data, and Knowledge Pub Date : 1900-01-01 DOI: 10.4230/OASIcs.LDK.2019.3

C. Chiarcos, Maxim Ionov

{"title":"Ligt: An LLOD-Native Vocabulary for Representing Interlinear Glossed Text as RDF","authors":"C. Chiarcos, Maxim Ionov","doi":"10.4230/OASIcs.LDK.2019.3","DOIUrl":"https://doi.org/10.4230/OASIcs.LDK.2019.3","url":null,"abstract":"The paper introduces Ligt, a native RDF vocabulary for representing linguistic examples as text with interlinear glosses (IGT) in a linked data formalism. Interlinear glossing is a notation used in various fields of linguistics to provide readers with a way to understand linguistic phenomena and to provide corpus data when documenting endangered languages. This data is usually provided with morpheme-by-morpheme correspondence which is not supported by any established vocabularies for representing linguistic corpora or automated annotations. Interlinear Glossed Text can be stored and exchanged in several formats specifically designed for the purpose, but these differ in their designs and concepts, and they are tied to particular tools, so the reusability of the annotated data is limited. To improve interoperability and reusability, we propose to convert such glosses to a tool-independent representation well-suited for the Web of Data, i.e., a representation in RDF. Beyond establishing structural (format) interoperability by means of a common data representation, our approach also allows using shared vocabularies and terminology repositories available from the (Linguistic) Linked Open Data cloud. We describe the core vocabulary and the converters that use this vocabulary to convert IGT in a format of various widely-used tools into RDF. Ultimately, a Linked Data representation will facilitate the accessibility of language data from less-resourced language varieties within the (Linguistic) Linked Open Data cloud, as well as enable novel ways to access and integrate this information with (L)LOD dictionary data and other types of lexical-semantic resources. In a longer perspective, data currently only available through these formats will become more visible and reusable and contribute to the development of a truly multilingual (semantic) web. 2012 ACM Subject Classification Information systems → Graph-based database models; Computing methodologies → Language resources; Computing methodologies → Knowledge representation and reasoning","PeriodicalId":377119,"journal":{"name":"International Conference on Language, Data, and Knowledge","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128232282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Towards Scope Detection in Textual Requirements 论文本需求中的范围检测

International Conference on Language, Data, and Knowledge Pub Date : 1900-01-01 DOI: 10.4230/OASIcs.LDK.2021.31

Ole Magnus Holter, Basil Ell

{"title":"Towards Scope Detection in Textual Requirements","authors":"Ole Magnus Holter, Basil Ell","doi":"10.4230/OASIcs.LDK.2021.31","DOIUrl":"https://doi.org/10.4230/OASIcs.LDK.2021.31","url":null,"abstract":"Requirements are an integral part of industry operation and projects. Not only do requirements dictate industrial operations, but they are used in legally binding contracts between supplier and purchaser. Some companies even have requirements as their core business. Most requirements are found in textual documents, this brings a couple of challenges such as ambiguity, scalability, maintenance, and finding relevant and related requirements. Having the requirements in a machinereadable format would be a solution to these challenges, however, existing requirements need to be transformed into machine-readable requirements using NLP technology. Using state-of-the-art NLP methods based on end-to-end neural modelling on such documents is not trivial because the language is technical and domain-specific and training data is not available. In this paper, we focus on one step in that direction, namely scope detection of textual requirements using weak supervision and a simple classifier based on BERT general domain word embeddings and show that using openly available data, it is possible to get promising results on domain-specific requirements documents. 2012 ACM Subject Classification Computing methodologies → Natural language processing","PeriodicalId":377119,"journal":{"name":"International Conference on Language, Data, and Knowledge","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130050392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Automatic Partitioning of Gutenberg.org Texts 古腾堡网站文本的自动分割

International Conference on Language, Data, and Knowledge Pub Date : 1900-01-01 DOI: 10.4230/OASIcs.LDK.2021.35

Davide Picca, Cyrille Gay-Crosier

引用次数: 1

Predicting Math Success in an Online Tutoring System Using Language Data and Click-Stream Variables: A Longitudinal Analysis 预测数学成功的在线辅导系统使用语言数据和点击流变量:纵向分析

International Conference on Language, Data, and Knowledge Pub Date : 1900-01-01 DOI: 10.4230/OASIcs.LDK.2019.25

S. Crossley, Shamya Karumbaiah, Jaclyn L. Ocumpaugh, Matthew J. Labrum, R. Baker

{"title":"Predicting Math Success in an Online Tutoring System Using Language Data and Click-Stream Variables: A Longitudinal Analysis","authors":"S. Crossley, Shamya Karumbaiah, Jaclyn L. Ocumpaugh, Matthew J. Labrum, R. Baker","doi":"10.4230/OASIcs.LDK.2019.25","DOIUrl":"https://doi.org/10.4230/OASIcs.LDK.2019.25","url":null,"abstract":"Previous studies have demonstrated strong links between students’ linguistic knowledge, their affective language patterns and their success in math. Other studies have shown that demographic and click-stream variables in online learning environments are important predictors of math success. This study builds on this research in two ways. First, it combines linguistics and click-stream variables along with demographic information to increase prediction rates for math success. Second, it examines how random variance, as found in repeated participant data, can explain math success beyond linguistic, demographic, and click-stream variables. The findings indicate that linguistic, demographic, and click-stream factors explained about 14% of the variance in math scores. These variables mixed with random factors explained about 44% of the variance. 2012 ACM Subject Classification Applied computing → Computer-assisted instruction; Applied computing → Mathematics and statistics; Computing methodologies → Natural language processing","PeriodicalId":377119,"journal":{"name":"International Conference on Language, Data, and Knowledge","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131831436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

A Review and Cluster Analysis of German Polarity Resources for Sentiment Analysis 面向情感分析的德语极性资源综述与聚类分析

International Conference on Language, Data, and Knowledge Pub Date : 1900-01-01 DOI: 10.4230/OASIcs.LDK.2021.37

B. Kern, Andreas Baumann, T. Kolb, Katharina Sekanina, Klaus Hofmann, Tanja Wissik, J. Neidhardt

引用次数: 2

On the Utility of Word Embeddings for Enriching OpenWordNet-PT 论词嵌入对OpenWordNet-PT的丰富作用

International Conference on Language, Data, and Knowledge Pub Date : 1900-01-01 DOI: 10.4230/OASIcs.LDK.2021.21

Hugo Gonçalo Oliveira, Fredson Silva de Souza Aguiar, Alexandre Rademaker

{"title":"On the Utility of Word Embeddings for Enriching OpenWordNet-PT","authors":"Hugo Gonçalo Oliveira, Fredson Silva de Souza Aguiar, Alexandre Rademaker","doi":"10.4230/OASIcs.LDK.2021.21","DOIUrl":"https://doi.org/10.4230/OASIcs.LDK.2021.21","url":null,"abstract":"The maintenance of wordnets and lexical knwoledge bases typically relies on time-consuming manual effort. In order to minimise this issue, we propose the exploitation of models of distributional semantics, namely word embeddings learned from corpora, in the automatic identification of relation instances missing in a wordnet. Analogy-solving methods are first used for learning a set of relations from analogy tests focused on each relation. Despite their low accuracy, we noted that a portion of the top-given answers are good suggestions of relation instances that could be included in the wordnet. This procedure is applied to the enrichment of OpenWordNet-PT, a public Portuguese wordnet. Relations are learned from data acquired from this resource, and illustrative examples are provided. Results are promising for accelerating the identification of missing relation instances, as we estimate that about 17% of the potential suggestions are good, a proportion that almost doubles if some are automatically invalidated. 2012 ACM Subject Classification Computing methodologies → Lexical semantics; Computing methodologies → Language resources","PeriodicalId":377119,"journal":{"name":"International Conference on Language, Data, and Knowledge","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123675885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Cherokee Syllabary Texts: Digital Documentation and Linguistic Description 切诺基音节文本:数字文档和语言描述

International Conference on Language, Data, and Knowledge Pub Date : 1900-01-01 DOI: 10.4230/OASIcs.LDK.2019.18

J. Bourns

引用次数: 2

Automatic Construction of Knowledge Graphs from Text and Structured Data: A Preliminary Literature Review 从文本和结构化数据中自动构建知识图谱:初步文献综述

International Conference on Language, Data, and Knowledge Pub Date : 1900-01-01 DOI: 10.4230/OASIcs.LDK.2021.19

Maraim Masoud, Bianca Pereira, John P. McCrae, P. Buitelaar

{"title":"Automatic Construction of Knowledge Graphs from Text and Structured Data: A Preliminary Literature Review","authors":"Maraim Masoud, Bianca Pereira, John P. McCrae, P. Buitelaar","doi":"10.4230/OASIcs.LDK.2021.19","DOIUrl":"https://doi.org/10.4230/OASIcs.LDK.2021.19","url":null,"abstract":"Knowledge graphs have been shown to be an important data structure for many applications, including chatbot development, data integration, and semantic search. In the enterprise domain, such graphs need to be constructed based on both structured (e.g. databases) and unstructured (e.g. textual) internal data sources; preferentially using automatic approaches due to the costs associated with manual construction of knowledge graphs. However, despite the growing body of research that leverages both structured and textual data sources in the context of automatic knowledge graph construction, the research community has centered on either one type of source or the other. In this paper, we conduct a preliminary literature review to investigate approaches that can be used for the integration of textual and structured data sources in the process of automatic knowledge graph construction. We highlight the solutions currently available for use within enterprises and point areas that would benefit from further research. 2012 ACM Subject Classification Information systems → Information extraction","PeriodicalId":377119,"journal":{"name":"International Conference on Language, Data, and Knowledge","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132272158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2