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Clique-based semantic kernel with application to semantic relatedness

2015 Natural Language Engineering  
Previous researches investigate the use of concept instead of word as a core semantic feature for incorporating semantic knowledge from an ontology into the representation model of documents.  ...  We concentrate on representing text documents and words using Wikipedia and WordNet, respectively.  ...  then used to enrich the representation of documents.  ... 
doi:10.1017/s135132491500008x fatcat:wdgfeteepffxtpd5thlzt3vu6y

Exploiting Semantic Annotations andQ-Learning for Constructing an Efficient Hierarchy/Graph Texts Organization

Asmaa M. El-Said, Ali I. Eldesoky, Hesham A. Arafat
2015 The Scientific World Journal  
, and to apply mining processes using the representation and the relatedness measure.  ...  This methodology is based on semantic notions to represent the text in documents, to infer unknown dependencies and relationships among concepts in a text, to measure the relatedness between text documents  ...  The semantic representations of textual documents determining the relatedness between them are evaluated by allowing clustering algorithms to use the produced relatedness matrix of the document set.  ... 
doi:10.1155/2015/136172 pmid:25685832 pmcid:PMC4313059 fatcat:wqrreslkb5bmdndexweesjuiry

Deep learning of knowledge graph embeddings for semantic parsing of Twitter dialogs

Larry Heck, Hongzhao Huang
2014 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)  
This paper presents a novel method to learn neural knowledge graph embeddings. The embeddings are used to compute semantic relatedness in a coherence-based semantic parser.  ...  A deep neural network approach known as Deep Structured Semantic Modeling (DSSM) is used to scale the approach to learn neural embeddings for all of the concepts (pages) of Wikipedia.  ...  learn neural KG embeddings, using these to compute semantic relatedness between mention-concept pairs.  ... 
doi:10.1109/globalsip.2014.7032187 dblp:conf/globalsip/HeckH14 fatcat:hrospi7f5ncmngv4p4bzuflhe4

An Efficient Information-Rich Representation Scheme for Information Access and Knowledge Acquisition

Asmaa El-Said, Hesham Arafat
2020 Bulletin of the Faculty of Engineering. Mansoura University  
and to apply mining processes using the representation and the relatedness measure.  ...  This approach is based on semantic notions to represent the text in documents, to infer unknown dependencies and relationships among concepts in a text, to measure the relatedness between text documents  ...  A new semantic relatedness measure is developed to determine the relatedness among concepts of the document as well as relatedness between contents of the documents for long/ short texts.  ... 
doi:10.21608/bfemu.2020.100775 fatcat:oytrcrqjabf3tbuftiax3mae3i


2011 International Journal of Semantic Computing (IJSC)  
The center of the approach relies on the use of a distributional semantic model to address the level of semantic interpretation demanded to build the data model independent approach.  ...  This article introduces a distributional structured semantic space which enables data model independent natural language queries over RDF data.  ...  Semantic relatedness The concept of semantic relatedness is described [10] as a generalization of semantic similarity, where semantic similarity is associated with taxonomic relations between concepts  ... 
doi:10.1142/s1793351x1100133x fatcat:4ws744oufnf65i632tpaqoapjq

Knowledge-Based Semantic Relatedness measure using Semantic features

Ali Muttaleb Hasan
2020 International Journal of Advanced Trends in Computer Science and Engineering  
Measuring semantic relatedness has received much attention for uses in many fields such as information retrieval and natural language processing.  ...  In this paper, the research framework is identified based on the observations made on the previous related works that have been conducted for semantic representation and semantic relatedness measures.  ...  Then, each set from the semantic representation of the first concept is compared to the corresponding setting from the semantic representation of the second concept using the cosine measure.  ... 
doi:10.30534/ijatcse/2020/02922020 fatcat:dynug7wu7zcnnn6q4mws77zpwm

Introducing Inter-Relatedness between Wikipedia Articles in Explicit Semantic Analysis [article]

Naveen Elango, Pawan Prasad K
2020 arXiv   pre-print
Explicit Semantic Analysis (ESA) is a technique used to represent a piece of text as a vector in the space of concepts, such as Articles found in Wikipedia.  ...  Especially we use an undirected Graph to represent this knowledge with nodes as Articles and edges as inter relations between two Articles.  ...  Explicit Semantic Analysis (ESA) ESA is a novel method in which semantic relatedness between words or documents are captured by representation of meaning in a high-dimensional space of natural concepts  ... 
arXiv:2012.00398v1 fatcat:z5al6syd5fdrdgbenj36j4p2ie

A Paper Recommendation System with ReaderBench: The Graphical Visualization of Semantically Related Papers and Concepts [chapter]

Ionut Cristian Paraschiv, Mihai Dascalu, Philippe Dessus, Stefan Trausan-Matu, Danielle S. McNamara
2015 Lecture Notes in Educational Technology  
Our previous analyses used the semantic representation of papers in different semantic models with the purpose of creating visual graphs based on the semantic relatedness links between the abstracts.  ...  The research includes a use case and its corresponding results by using interactive and exploratory network graph representations.  ...  Figure 1 . 1 Network graph of the semantically related documents to the input query. Figure 2 . 2 Concept map of query concepts and semantically related words.  ... 
doi:10.1007/978-981-287-868-7_53 fatcat:7edbyyr5gvf27fqml76l5yscdm

Social Semantics and Its Evaluation by Means of Semantic Relatedness and Open Topic Models

Ulli Waltinger, Alexander Mehler
2009 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology  
We propose a feature-frequency-based method for measuring semantic relatedness which is needed in order to reduce the number of document features for the task of topic labelling.  ...  This paper presents an approach using social semantics for the task of topic labelling by means of Open Topic Models.  ...  Additionally, we proposed a method for measuring semantic relatedness using a reduced vector representation of the Wikipedia document collection.  ... 
doi:10.1109/wi-iat.2009.14 dblp:conf/webi/WaltingerM09 fatcat:ipcyemzd6bdbxbxlntq5elhr34

A systematic study of knowledge graph analysis for cross-language plagiarism detection

Marc Franco-Salvador, Paolo Rosso, Manuel Montes-y-Gómez
2016 Information Processing & Management  
Finally, as a key component of the knowledge graph construction, we present a new weighting scheme of relations between concepts based on distributed representations of concepts.  ...  In this paper, we perform a systematic examination of Cross-language Knowledge Graph Analysis; an approach that represents text fragments using knowledge graphs as a language independent content model.  ...  Distributed representations for conceptual semantic relatedness We introduce a new weighting scheme, based on the use of distributed representations of concepts, to measure the semantic relatedness between  ... 
doi:10.1016/j.ipm.2015.12.004 fatcat:v44kzogvmffdvaego56qijxzwq

Graph-based Methods for Significant Concept Selection

Gasmi Karim, Torjmen-Khemakhem Mouna, Tamine Lynda, Ben Jemaa Maher
2015 Procedia Computer Science  
More specifically, we build the graph whose nodes represented concepts and weighted edges represent semantic distances.  ...  Concept-based representation of both the document and the query is one of the most effective approaches that lowers the effect of text mismatch and allows the selection of relevant documents that deal  ...  In most of works that use the graph-based representation 23, 25 , only one semantic relation between concepts is assumed to be accurate and used to compute the importance of their relatedness.  ... 
doi:10.1016/j.procs.2015.08.170 fatcat:jyrbhs444rez7nxzggvw3726a4

A novel semantic level text classification by combining NLP and Thesaurus concepts

R. Nagaraj
2014 IOSR Journal of Computer Engineering  
In the previous approaches only the Wikipedia concepts related to terms in syntactic level are used to represent document in semantic level.  ...  The semantic weight of terms related to the concepts from Wikipedia and Word Net are used to represent semantic information.  ...  However, these methods do not use the contextual semantic relatedness to change the concept weight.  ... 
doi:10.9790/0661-16461426 fatcat:2diyndiwdnfutaoswlj3bqklpq

Learning a concept-based document similarity measure

Lan Huang, David Milne, Eibe Frank, Ian H. Witten
2012 Journal of the American Society for Information Science and Technology  
We propose a new measure that assesses similarity at both the lexical and semantic levels, and learns from human judgments how to combine them by using machine learning techniques.  ...  Conventional measures are brittle: they estimate the surface overlap between documents based on the words they mention and ignore deeper semantic connections.  ...  Concept Relatedness Measure Measuring semantic relatedness between concepts is a challenging research problem in its own right and has been studied extensively using both WordNet and Wikipedia (Resnik  ... 
doi:10.1002/asi.22689 fatcat:o55ahze4izdpbk7ugbaydrlzfy

An Approach for Discovering and Exploring Semantic Relationships between Genes

Nicoletta Dessì, Matteo Pani, Barbara Pes, Diego Reforgiato Recupero
2017 Extended Semantic Web Conference  
It includes: i) a method for extracting annotations from several ontologies, mapping them into concepts and evaluating the semantic relatedness of genes, ii) the definition of a NoSQL graph database that  ...  leverages a loosely structured and multifaceted organization of data for storing concepts and their relationships, and iii) a mechanism to support the customized exploration of stored information.  ...  In particular, graph databases support data representation in a graph structure where nodes denote biomedical concepts and edges between nodes represent their relationships.  ... 
dblp:conf/esws/DessiPPR17 fatcat:dz2xu3dleja3ppn4cmtunw4af4

Semantic Similarity Estimation using Vector Symbolic Architectures

Job Isaias Quiroz-Mercado, Ricardo Barron-Fernandez, Marco Antonio Rammirez-Salinas
2020 IEEE Access  
In this paper, we propose a model whose representations are based on the semantic features associated with a concept within the ConceptNet knowledge graph.  ...  In addition to word distribution, these vector representations consider several types of information.  ...  VSA has been used for concept representation [58] .  ... 
doi:10.1109/access.2020.3001765 fatcat:tdrzmk4rhnhbhekelri5b6aepi
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