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A Proposed Method for Semantic Annotation on Social Media Images

Mrs. Sayantani Ghosh, Prof. Samir K. Bandyopadhyay
2017 International Journal Of Engineering And Computer Science  
Many researchers believe semantic annotations can be inserted in web-based documents for information extraction and knowledge mining. These annotations use terms defined in an ontology.  ...  This paper uses the annotation process based on textual patterns for improving annotation.  ...  Structured knowledge models, such as semantic hierarchies and ontologies, will be a good way to improve such approaches.  ... 
doi:10.18535/ijecs/v6i6.31 fatcat:pifx6v52lbcyfhgshdqq2rr6nq

Automatic knowledge extraction from manufacturing research publications

P. Boonyasopon, A. Riel, W. Uys, L. Louw, S. Tichkiewitch, N. du Preez
2011 CIRP annals  
Knowledge mining is a young and rapidly growing discipline aiming at automatically identifying valuable knowledge in digital documents.  ...  This paper presents the results of a study of the application of document retrieval and text mining techniques to extract knowledge from CIRP research papers.  ...  keywords more difficult and cumbersome.  ... 
doi:10.1016/j.cirp.2011.03.043 fatcat:ecob3mbalvfppj5opwo7fivegi

Extraction of Relevant Resources and Questions from DBpedia to Automatically Generate Quizzes on Specific Domains [chapter]

Oscar Rodríguez Rocha, Catherine Faron Zucker, Alain Giboin
2018 Lecture Notes in Computer Science  
However, automatically extracting from the LOD a knowledge graph composed by the information of a set of resources which are relevant to a given specific domain or topic, is a crucial phase for the automatic  ...  To address this issue, we propose a heuristic that extracts from DBpedia a set of resources related to a given specific domain.  ...  In [4] [6] [7] , the authors describe an approach to exploit semantic relations stored in the DBpedia dataset to extract and rank resources related to the user context given by the keywords she enters  ... 
doi:10.1007/978-3-319-91464-0_43 fatcat:sjjzwqv455cxzebwxkqtgmjmlq

Predicting Abstract Keywords by Word Vectors [chapter]

Qing Li, Wenhao Zhu, Zhiguo Lu
2016 Lecture Notes in Computer Science  
The results show that the method can improve the accuracy of the phrase keyword extraction and find the keywords not appearing in the text.  ...  The Euclidean distances between every candidate words and every text words are calculated to find out the top-N-closest keywords as the automatic text extraction keywords.  ...  automatic keywords extraction is greatly improved compared to the previous method.  ... 
doi:10.1007/978-3-319-32557-6_20 fatcat:2jj2v63wkvabxbnoviyuvcvxy4

Automatic Concept Extraction in Semantic Summarization Process [chapter]

Antonella Carbonaro
2012 Advances in Knowledge Representation  
steps in exploring automatic concept extraction in semantic summarization process.  ...  Table 3 . 3 Automatically extracted articles representing [MW08] www.intechopen.comAdvances in Knowledge Representation www.intechopen.comAutomatic Concept Extraction in Semantic Summarization  ...  Automatic Concept Extraction in Semantic Summarization Process, Advances in Knowledge Representation, Dr.  ... 
doi:10.5772/37160 fatcat:wcuqgupgbfeyrmdmw56nlpykfi

Finding Hidden Semantics Behind Reference Linkages : An Ontological Approach for Scientific Digital Libraries [chapter]

Peixiang Zhao, Ming Zhang, Dongqing Yang, Shiwei Tang
2005 Lecture Notes in Computer Science  
Moreover, implicit semantics behind reference indices are mined and organized to improve accessibility of scientific papers.  ...  Compared with abstract of a specific paper written by authors themselves, we introduce an automatic summary generation algorithm to create objective descriptions from other scholars' perspectives based  ...  However, as the availability of scientific literature greatly improves, the inability of people to disseminate, share and profitably utilize such a large amount of information becomes more and more severe  ... 
doi:10.1007/11408079_64 fatcat:ch6rilf7rfarpk4uhvewdxhmsi

Deriving Semantic Sessions from Semantic Clusters

Banafsheh Safarkhani, Mojde Talabeigi, Mehran Mohsenzadeh, Mohammad Reza Meybodi
2009 2009 International Conference on Information Management and Engineering  
Our contribution is that we introduce a mechanism to automatically improve the representation of the user in the website using a comprehensive lexical semantic resource and semantic clusters.  ...  This process engendered to improving deriving semantic sessions from web site user page views.  ...  The main difference of it with previous works is its fully automatic concept extraction mechanism using a much more comprehensive lexical semantic resource.  ... 
doi:10.1109/icime.2009.131 fatcat:fugjmghp3jaj7ha4unezbjhf3a

Collaborative Semantic Annotation of Images : Ontology-Based Model

Damien E. ZOMAHOUN
2013 Signal & Image Processing An International Journal  
Others have resorted to the integration of images analysis improvement knowledge and images interpretation using ontologies.  ...  In the quest for models that could help to represent the meaning of images, some approaches have used contextual knowledge by building semantic hierarchies.  ...  Ontology can be directly processed by a machine, and at the same time can help to extract implicit knowledge through automatic inference [29] , [30] .  ... 
doi:10.5121/sipij.2013.4606 fatcat:kr3b4last5eyjcho65yhzdawom

Text mining based knowledge management in banking [chapter]

K. Lebeth, M. Lorenz, U. Störl
2005 Text Mining and its Applications to Intelligence, CRM and Knowledge Management  
This paper presents a text mining based knowledge management (KM) approach.  ...  After a short introduction, we describe our idea of an integrated knowledge management infrastructure, using natural language technology as a main building block to enable the sharing of knowledge with  ...  On the other hand we enable the automatic enrichment of documents, using term extraction methods and term frequency analysis to provide the most important keywords that might describe a given document  ... 
doi:10.2495/978-1-85312-995-7/16 fatcat:pxd4j7vv5vamfpl6ukfudj5fwy

The Impact of Online Indexing in Improving Arabic Information Retrieval Systems

Tahar Dilekh, Saber Benharzallah, Ali Behloul
2018 Informatica (Ljubljana, Tiskana izd.)  
In addition, this model is more efficient as it helps minimizing index storage size, consequently, improving the response time of the different requests.  ...  The proposed method of indexing belongs to semi-automatic category of indexing and consists of two types.  ...  We then present some work related to the automatic Arabic keyword extraction, which helps to improve the quality of Arabic indexing systems.  ... 
doi:10.31449/inf.v42i4.2297 fatcat:elbuqblm45adjd7jwm6dhywwje

Jump-starting a Body-of-Knowledge with a Semantic Wiki on a Discipline Ontology

Víctor Codocedo, Claudia López, Hernán Astudillo
2010 Semantic Wiki Workshop  
Several communities have engaged recently in assembling a Body of Knowledge (BOK) to organize the discipline knowledge for learning and sharing.  ...  BOK ideally represents the domain, contextualizes assets (e.g. literature), and exploits the Social Web potential to maintain and improve it.  ...  Semantic Wiki Semantic Wikis are designed to allow collaborative creation of content using a fixed syntax and semantics to improve searching and querying.  ... 
dblp:conf/semwiki/CodocedoLA10 fatcat:q7jf674wrzclbobl2da24ucuzi

An Ontology-Based Information Retrieval Model [chapter]

David Vallet, Miriam Fernández, Pablo Castells
2005 Lecture Notes in Computer Science  
Semantic search is combined with keyword-based search to achieve tolerance to KB incompleteness.  ...  Our proposal is illustrated with sample experiments showing improvements with respect to keyword-based search, and providing ground for further research and discussion.  ...  A few more documents where semantic search alone fails are still given a high ranking thanks to the combination with keyword-search, which shows here a comparable behavior to example a. Query c.  ... 
doi:10.1007/11431053_31 fatcat:ok7fxqm4w5eqdogdvoyvfavkqq

Towards an Iterative Reinforcement Approach for Simultaneous Document Summarization and Keyword Extraction

Xiaojun Wan, Jianwu Yang, Jianguo Xiao
2007 Annual Meeting of the Association for Computational Linguistics  
The corpus-based approach is validated to work almost as well as the knowledge-based approach for computing word semantics.  ...  Though both document summarization and keyword extraction aim to extract concise representations from documents, these two tasks have usually been investigated independently.  ...  Keyword extraction is the process of extracting a few salient words (or phrases) from a given text and using the words to represent the text.  ... 
dblp:conf/acl/WanYX07 fatcat:bqgax2lrbbgljbgj6mdwtgahja

HISA: A Query System Bridging The Semantic Gap For Large Image Databases

Gang Chen, Xiaoyan Li, Lidan Shou, Jinxiang Dong, Chun Chen
2006 Very Large Data Bases Conference  
Using these techniques, HISA is able to bridge the gap between the image semantics and the visual features, therefore providing more user-friendly and high-performance queries.  ...  HISA employs automatic image annotation technique, ontology analysis and statistical analysis of domain knowledge to precompute the data structure.  ...  In this way, our automatic annotation method is more reliable and robust.  ... 
dblp:conf/vldb/ChenLSDC06 fatcat:mi6qfzj7orb2xekjty6z6cvugm

Hybrid Fuzzy-ontology Design Using FCA Based Clustering for Information Retrieval in Semantic Web

K. Balasubramaniam
2015 Procedia Computer Science  
The given algorithm is a hybrid technique based on matching extracted instances from the input queries and in information domain.  ...  Introducing the ontology knowledge provides more relevant search results for the users information need.  ...  Since these attributes are descriptors for the generated clusters, if more keywords are extracted and used, the more meaningful the cluster descriptors are constructed.  ... 
doi:10.1016/j.procs.2015.04.075 fatcat:lapkeusytzfirharigor2ntnca
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