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Contextual Text Mining Framework for Unstructured Textual Judicial Corpora through Ontologies
2022
Computer systems science and engineering
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Text mining helps to analyze and search different court cases available in the form of digital text documents to extract case reasoning and related data. ...
Mining context information through ontologies from corpora is a challenging and interesting field. ...
Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study. ...
doi:10.32604/csse.2022.025712
fatcat:ey4awnzatrattctyv4yfmewfoi
Fuzzy Cross Domain Concept Mining
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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Initially, we have extracted important concepts from unstructured data followed by generation of vector space of each concept. ...
Then clustering them in based on their distances ...
Concept maps can be created from textual and non-textual sources, e.g. concept maps for Croatian language has been given in [41] . ...
doi:10.35940/ijitee.j1059.08810s19
fatcat:fwwcqjzofzaxfa2u3br4nx4a6u
Investigating contextual ontologies and document corpus characteristics for information access in engineering settings
2017
Journal of IT Cases and Applications
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However, identifying relevant information from a rapidly growing number of unstructured resources is challenging for users. ...
We provide an indepth analysis of document corpus characteristics of this real-life shared engineering workspace to understand the content and context of documents using information retrieval methods and ...
Although no textual content is extracted from documents of this group, fields of document name and path contain useful content to make a group of non-textual documents retrievable by ontology concepts. ...
doi:10.1080/15228053.2017.1313557
fatcat:n2hdwklppnfipk5iz5fgpqrjna
Semantic Annotation of Unstructured Documents Using Concepts Similarity
2017
Scientific Programming
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In this proposal, ontologies are used to determine the context of the entities specified in the query. Our strategy for extracting the context is focused on concepts similarity. ...
Some proposals take into account the contextual meaning of the terms specified in the query. Semantic annotation technique can help to retrieve and extract information in unstructured documents. ...
Given a document and a knowledge base, the objective of this phase is to extract the textual descriptions and the semantic context of all the information about from the knowledge base. ...
doi:10.1155/2017/7831897
fatcat:xwtg2olauben7hlsq5ab77ytmy
Predictive Business Process Monitoringwith Context Information from Documents
2019
European Conference on Information Systems
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In this paper, we argue that process-related unstructured documents are also a promising source for extracting processcontext data. ...
Accordingly, this research-in-progress paper outlines a design-science research process for creating a predictive business process monitoring technique that utilizes context data from process-related documents ...
Teinemaa et al. ( 2016 ) use unstructured context information from emails and comments. However, no work considers context information from process-attached documents. ...
dblp:conf/ecis/WeinzierlRM19
fatcat:qyzw54fr6fa47bqdsrbf6thd6e
Ontology Learning Process as a Bottom-up Strategy for Building Domain-specific Ontology from Legal Texts
2017
Proceedings of the 9th International Conference on Agents and Artificial Intelligence
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Ontologies can be learnt from various sources, such as databases, structured and unstructured documents. Here, the focus is on the acquisition of ontologies from unstructured text, provided as input. ...
The objective of this paper is to present the role of Ontology Learning Process in supporting an ontology engineer for creating and maintaining ontologies from textual resources. ...
ACKNOWLEDGEMENTS This project has been funded with support from the European Union with the European Regional Development Fund (ERDF), the National Support from the National Council for Scientific Research ...
doi:10.5220/0006188004730480
dblp:conf/icaart/GhoshNAK17
fatcat:itgy6dfs2ra2rf6ivz3p3uibyu
On Cohort Retrieval System from Clinical Data Repositories using OMOP Common Data Model: A Proof-of-Concept Implementation (Preprint)
2019
JMIR Medical Informatics
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The natural language processing component was used to extract common data model concepts from textual queries. ...
of Text from Electronic Health Records (CREATE). ...
The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. ...
doi:10.2196/17376
pmid:33021486
fatcat:jnr452ywrzbuhajeamukcb4aqi
Cross Media Entity and Concept Driven Search
2016
International Conference on Semantic Systems
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This paper describes the process of automated semantic information extraction from multimedia documents, which is central in developing concept and entity driven search across different media types. ...
This paper presents Sensefy -a cross media information retrieval system, which uses higher-level semantic concepts and entities for retrieving documents of different media types. ...
Real Madrid C.F.) and concepts (e.g. soldier) from unstructured text, including text streams extracted from audio and video files. ...
dblp:conf/i-semantics/PereraJ16
fatcat:kqbn2taapndw5grs4h5fv5biya
A Framework for Capturing and Analyzing Unstructured and Semi-structured Data for a Knowledge Management System
[article]
2020
arXiv
pre-print
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Unlike most frameworks published in the literature that focuses on a specific type of unstructured data, our frameworks cut across the varieties of unstructured data ranging from textual data from social ...
Mainstream knowledge management researchers generally agree that knowledge extracted from unstructured data and semi-structured data have become imperative for organizational strategic decision making. ...
Concept Extraction technique results in the extraction of concepts from the text. A common technique for concept extraction is the use of Word Tree. ...
arXiv:2007.07102v1
fatcat:lopo3a6bozbdrj4oudoz3bq2p4
A Framework for Semantic Text Clustering
2020
International Journal of Advanced Computer Science and Applications
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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. ...
The goal is to exploit these techniques to the full usage of the Resource Description Framework (RDF) to represent textual data as triplets. ...
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
Bringing Shape to Textual Data – A Feasible Demonstration
2019
Mehran University Research Journal of Engineering and Technology
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This has led towards immense amount of unstructured data (i.e. textual data), which is a major source to get useful knowledge about people in several application domains. ...
TM (Text Mining) extracts high quality information to discover knowledge by drawing patterns and relationships in textual data. This field has taken great attention of the research community. ...
ACKNOWLEDGMENTS The authors wish to thank continued support of the ...
doi:10.22581/muet1982.1904.04
fatcat:yackjesnjvbmlgohnpcyofypiu
Business applications of unstructured text
2007
Communications of the ACM
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Following [10] , this architecture distinguishes document-based processing from concept-based processing. ...
Concept-based processing usually analyzes a corpus for relationships among concepts in document content. Links to documents are returned only as corroborating evidence of the concept-based results. ...
doi:10.1145/1290958.1290967
fatcat:udwl7da6czfjhc34oypfnoq624
Text Mining Technique for Driving Potentially Valuable Information from Text
2020
Information and Knowledge Management
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Text mining can be a huge benefit for finding relevant and desired text data from unstructured data sources. ...
Text Mining is the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources. ...
Information Extraction is the process of automatically obtaining structured data from an unstructured natural language document. ...
doi:10.7176/ikm/10-1-01
fatcat:z45wuvxfgfg7zcwu56iwb5vh2a
A literature review on the state-of-the-art in patent analysis
2014
World Patent Information
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The rapid growth of patent documents has called for the development of sophisticated patent analysis tools. ...
This literature review presents the state-of-the-art in patent analysis and also presents taxonomy of patent analysis techniques. ...
Her research interests include context-based Web search, virtual team collaboration, and using technology to support competitive intelligence and decision-making. ...
doi:10.1016/j.wpi.2013.12.006
fatcat:prs6spbuhfd6lheiocbw5jz3di
Framework for Interrogative Knowledge Identification
2009
Computer and Information Science
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This research is an experimental approach using an appropriate test collection of unstructured documents. A system was developed based on the Interrogative Knowledge Identification framework. ...
This is to improve better understanding the process of making sense the information or knowledge residing in unstructured documents. ...
It is also used to extract interrogative lexical constructs from the individual unstructured document. iii. ...
doi:10.5539/cis.v2n4p109
fatcat:bij4p5qq3bgvjns4733lc7oxbe
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