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An Overview of Textual Semantic Similarity Measures Based on Web Intelligence

Jorge Martinez
2017 Figshare  
These techniques use some kinds of web intelligence to determine the degree of similarity between text expressions.  ...  The problem is that traditional approaches to semantic similarity measurement are not suitable for all situations, for example, many of them often fail to deal with terms not covered by synonym dictionaries  ...  Introduction Textual semantic similarity measurement consists of computing the similarity between terms, statements or texts, which have the same meaning, but which are not lexicographically similar [  ... 
doi:10.6084/m9.figshare.5624875.v1 fatcat:cmz6qja4bffhpgsqr3rjkjpkxu

An Overview of Textual Semantic Similarity Measures Based on Web Intelligence

J. M. Gil
2018 Figshare  
These techniques use some kinds of web intelligence to determine the degree of similarity between text expressions.  ...  The problem is that traditional approaches to semantic similarity measurement are not suitable for all situations, for example, many of them often fail to deal with terms not covered by synonym dictionaries  ...  Introduction Textual semantic similarity measurement consists of computing the similarity between terms, statements or texts, which have the same meaning, but which are not lexicographically similar [  ... 
doi:10.6084/m9.figshare.6541892.v1 fatcat:5i2anglbabesnkzrvmhq4ckl5e

An overview of textual semantic similarity measures based on web intelligence

Jorge Martinez-Gil
2012 Artificial Intelligence Review  
These techniques use some kinds of web intelligence to determine the degree of similarity between text expressions.  ...  The problem is that traditional approaches to semantic similarity measurement are not suitable for all situations, for example, many of them often fail to deal with terms not covered by synonym dictionaries  ...  Introduction Textual semantic similarity measurement consists of computing the similarity between terms, statements or texts, which have the same meaning, but which are not lexicographically similar [  ... 
doi:10.1007/s10462-012-9349-8 fatcat:23rehdw7ijholnwjrsvtzitauy

Application of Natural Language Processing and Evidential Analysis to Web-Based Intelligence Information Acquisition

Natalia Danilova, David Stupples
2012 2012 European Intelligence and Security Informatics Conference  
However, they cannot currently be effectively applied to Web-based search due to various obstacles, such as lack of semantic tagging.  ...  This information may be retrieved from an organization's knowledge base (Intranet) or from the World Wide Web.  ...  Further analysis of the results shows that an intelligence knowledge base will be greatly enhanced from a richness viewpoint, if the focus of intelligence analysts is on identifying 'UUs'.  ... 
doi:10.1109/eisic.2012.41 dblp:conf/eisic/DanilovaS12 fatcat:vr7rtl6gang3pepo4e6w4bem3e

A Framework for Semantic Text Clustering

Soukaina Fatimi, Chama EL, Larbi Alaoui
2020 International Journal of Advanced Computer Science and Applications  
It also highlights the advantages of using semantic web techniques in clustering, subject modeling and knowledge extraction based on processes of questioning, reasoning and inferencing.  ...  Since Text clustering is an indispensable task for better exploitation of documents, the use of documents may be more intelligently conducted while considering semantics in the process of text clustering  ...  We present an overall framework, and show how to apply machine learning techniques to mine textual documents using This work is within the framework of the research project "Big Data Analytics -Methods  ... 
doi:10.14569/ijacsa.2020.0110657 fatcat:undy4wffzvgkxiopyhtys64zuu

Introduction: Modeling, Learning and Processing of Text-Technological Data Structures [chapter]

Alexander Mehler, Kai-Uwe Kühnberger, Henning Lobin, Harald Lüngen, Angelika Storrer, Andreas Witt
2011 Studies in Computational Intelligence  
Acknowledgement Like its predecessor "'Linguistic Modeling of Information and Markup Languages" [11] , this book is based on contributions and numerous discussions at a corresponding conference at the  ...  In the case of the present volume, this relates to the conference on "Processing Text-Technological Resources", organized by the research group "Text-technological  ...  In their chapter, "Semantic distance measures with distributional profiles o f coarse-grained concepts", Graeme Hirst and Saif Mohammad first provide an overview of NLP applications using such measures  ... 
doi:10.1007/978-3-642-22613-7_1 fatcat:4moj7owrc5ec5msnvw5fqyc7sy

Emerging Trends in Reducing Semantic Gap towards Multimedia Access: A Comprehensive Survey

Aijazahamed Qazi, R. H. Goudar
2016 Indian Journal of Science and Technology  
Findings: This paper provides an overview of contemporary challenges and open research issues in reducing the Semantic gap.  ...  Semantic web is combined with statistical and machine learning techniques to increase the efficiency of an information retrieval system.  ...  The proposed approach introduces a system to associate textual description of an image by classifying them into semantic classes based on their visual features to reduce semantic gap.  ... 
doi:10.17485/ijst/2016/v9i30/99072 fatcat:asnamx3urveabjyritsri3guuy

Using Similarity Measures for Context-Aware User Interfaces

Melanie Hartmann, Torsten Zesch, Max Mühlhäuser, Iryna Gurevych
2008 2008 IEEE International Conference on Semantic Computing  
In this paper, we present an approach for the representation extraction task that outperforms existing ones, and we explore the potential of similarity measures for the context mapping task.  ...  We address this problem for web applications by (i) automatically extracting a textual representation of their input elements, and by (ii) mapping context information to them using these textual representations  ...  This work was also carried out as part of the project "Semantic Information Retrieval from Texts in the Example Domain Electronic Career Guidance" (SIR) funded by the German Research Foundation under the  ... 
doi:10.1109/icsc.2008.94 dblp:conf/semco/HartmannZMG08 fatcat:iyexx3gkvvet3hwhzxxtodr3ri

A survey on how to cross-reference web information sources

Joe Raad, Aurelie Bertaux, Christophe Cruz
2015 2015 Science and Information Conference (SAI)  
this kind of similarity measure, all approaches measure similarity based on the information content of each concept.  ...  (and reversely). 4) Distributional based measures: In this kind of approaches, similarity measure is based on the assumption that semantically close terms tend to appear in similar context.  ... 
doi:10.1109/sai.2015.7237206 fatcat:syhjn5vvkzhptcvmd4wc34v3ue

Knowledge Based Summarization and Document Generation using Bayesian Network

Shrikant Malviya, Uma Shanker Tiwary
2016 Procedia Computer Science  
research article based on the query given by a user.  ...  Semantic Tree stores all the textual units with their score in nodes organized at different levels depending on their type such as at the bottom leaf nodes keep the words with its probability, the upper  ...  using Concept Space and Cosine Similarity Measurement Web Link From Numbers to Symbols to Knowledge Structures: Artificial Intelligence Perspectives on the Classification Task Web Link Optimization of  ... 
doi:10.1016/j.procs.2016.06.080 fatcat:zq6mitvfvvhy5juhmn4afu4tte

Recognizing Textual Entailment by Generality Using Informative Asymmetric Measures and Multiword Unit Identification to Summarize Ephemeral Clusters

Gaël Dias, Sebastiao Pais, Katarzyna Wegrzyn-Wolska, Robert Mahl
2011 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology  
In particular, the AISs proposes an unsupervised language-independent solution to infer Textual Entailment by Generality and as such can help to encounter the web snippet with maximum semantic coverage  ...  This new methodology is tested against the first Recognizing Textual Entailment data set (RTE-1) 1 for an exhaustive number of asymmetric association measures with and without the identification of Multiword  ...  based on similar assumptions.  ... 
doi:10.1109/wi-iat.2011.122 dblp:conf/webi/DiasPWM11 fatcat:ihe2wvawwfallnfo2sct6knkfi

Kernel Canonical Correlation with Similarity Refinement for Automatic Image Tagging

Yanhui Xiao, Yao Zhao, Zhenfeng Zhu
2010 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing  
In this paper, we propose an AIT method based on kernel canonical correlation analysis (KCCA) with similarity refinement (KCCSR).  ...  Different from the previous KCCA based tagging methods, the graph based similarity refinements are first implemented by an interactive way to obtain the enhanced visual and textual representations.  ...  KCCSR BASED TAGGING SCHEME Figure 1 illustrates the overview of our KCCSR method and the overall work is composed of three parts.  ... 
doi:10.1109/iihmsp.2010.145 dblp:conf/iih-msp/XiaoZZ10 fatcat:wjeqhvow7nh63lpwnaze5obokm

Adding Semantics to Business Intelligence: Towards a Smarter Generation of Analytical Tools [chapter]

Denilson Sell, Dhiogo Cardoso da Silva, Fernando Benedet, Mrcio Napoli, Jos Leomar
2012 Business Intelligence - Solution for Business Development  
In this chapter, we describe how Semantic Web technologies and business semantics were applied on the conception of an architecture for analytical tools.  ...  Just as the Semantic Web provides agile ways and navigation interfaces based on high semantic expressiveness to locate relevant content on the Internet, BI architectures must also make use of semantic  ...  This book presents both an overview of Business Intelligence and an in-depth analysis of current applications and future directions for this technology.  ... 
doi:10.5772/35572 fatcat:pcy3f2ymyjclrkwx2ficgosvri

Cross-media analysis and reasoning: advances and directions

Yu-xin Peng, Wen-wu Zhu, Yao Zhao, Chang-sheng Xu, Qing-ming Huang, Han-qing Lu, Qing-hua Zheng, Tie-jun Huang, Wen Gao
2017 Frontiers of Information Technology & Electronic Engineering  
Cross-media analysis and reasoning is an active research area in computer science, and a promising direction for artificial intelligence.  ...  To address these issues, we provide an overview as follows: (1) theory and model for cross-media uniform representation; (2) cross-media correlation understanding and deep mining; (3) cross-media knowledge  ...  , textual, and semantics cues.  ... 
doi:10.1631/fitee.1601787 fatcat:dqnizhdlbfhpvodzkhv5nlarxq

Discovering Image-Text Associations for Cross-Media Web Information Fusion [chapter]

Tao Jiang, Ah-Hwee Tan
2006 Lecture Notes in Computer Science  
Specifically, we employ a similarity-based multilingual retrieval model and adopt a vague transformation technique for measuring the information similarity between visual features and textual features.  ...  The diverse and distributed nature of the information published on the World Wide Web has made it difficult to collate and track information related to specific topics.  ...  Measuring similarity between visual and textual features is similar to the task of measuring relevance of documents in the field of multilingual retrieval for selecting documents in one language based  ... 
doi:10.1007/11871637_56 fatcat:e2xsgpcfwvaoxmw72fwxpt43x4
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