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A Computational Modeling for Knowledge Binding of the Unstructured Web Data

The focus of this manuscript is laid towards extracting insightful data embedded into web-based information which is crucial for various academic and commercialized application requirements.  ...  The study thereby introduces a robust computational modeling by means of computing knowledge from collaborative web-based unstructured information.  ...  graph mining is a technique which is explored very less.  ... 
doi:10.35940/ijitee.b1041.1292s19 fatcat:rovekujq6rhghjpefilyn5n4ea

Search Ranking for Heterogeneous Data over Dataspace

Niranjan Lal, Samimul Qamar, Savita Shiwani
2016 Indian Journal of Science and Technology  
Traditional relational database systems queries works over structured data, whereas information retrieval systems are designed for additional versatile and flexible ranked keyword queries, works over unstructured  ...  We also investigate how structured, semi structured or unstructured data can be take advantages for ranking of search on Web and Dataspace with their research challenges.  ...  Existing models target on exploring relational databases and data-centric XML information.  ... 
doi:10.17485/ijst/2016/v9i36/102055 fatcat:gy27vx6kmrdu3czlp6hd5dyx54

Improving confidence while predicting trends in temporal disease networks [article]

Djordje Gligorijevic, Jelena Stojanovic, Zoran Obradovic
2018 arXiv   pre-print
Our experiments demonstrate benefits of using graph information in modeling temporal disease properties as well as improvements in uncertainty estimation provided by given extensions of the Gaussian Conditional  ...  Quality of uncertainty estimation is a subject of over or under confident prediction, which is often not addressed in many models.  ...  Healthcare Cost and Utilization Project (HCUP), Agency for Healthcare Research and Quality, provided data used in this study.  ... 
arXiv:1803.11462v1 fatcat:bdkspynbunawxhtrin75ciunm4

A Framework for Semantic Text Clustering

Soukaina Fatimi, Chama EL, Larbi Alaoui
2020 International Journal of Advanced Computer Science and Applications  
The framework allows documents RDF representation, clustering, topic modeling, clusters summarizing, information retrieval based on RDF querying and Reasoning tools.  ...  To come up a more effective clustering method, we provide a semantic representation of the data in texts on which the clustering process would be based.  ...  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

Relationship Web: Spinning the Web from Trailblazing to Semantic Analytics [chapter]

Amit Sheth
2008 Lecture Notes in Computer Science  
manually, semi-automatically and automatically) and gleaned from • Structured data (e.g., NCBI databases) • Semi-structured data (e.g., XML based and semantic metadata standards for domain specific data  ...  and Services Science Semantic Trail Knowledge Enabled Information and Services Science Semantic Trails over all types of Data Semantic Trails can be built over a Web of Semantic (Meta)Data extracted (  ...  , structured (eg, databases) data and data of various modalities (eg, sensor data, biomedical experimental data).  ... 
doi:10.1007/978-3-540-87877-3_2 fatcat:fkkpyyr2kfh2vjjocs35t44x7u

Graph Data: The Next Frontier in Big Data Modeling for Various Domains

Angira Amit Patel, Jyotindra Dharwa
2017 Indian Journal of Science and Technology  
This investigation anticipates use of an appropriate graph structure and provides guidelines for solving data modeling challenges for structure, semi structure and unstructured data.  ...  Extensive literature review demonstrates use of diversified graph structures as means of data storage and analysis as it can cope up any kind of complex structures ranging from multi linked web data, complex  ...  over the network using graph based representation 14 .  ... 
doi:10.17485/ijst/2017/v10i21/112828 fatcat:7qprb6pdxrc3hpv4sk3olu4kmi

A Framework for the Forensic Investigation of Unstructured Email Relationship Data

John Haggerty, Alexander J. Karran, David J. Lamb, Mark Taylor
2011 International Journal of Digital Crime and Forensics  
Emails comprise both structured and unstructured data. Structured data provides qualitative information to the forensics examiner and is typically viewed through existing tools.  ...  Unstructured data is more complex as it comprises information associated with social networks, such as relationships within the network, identification of key actors and power relations, and there are  ...  from both structured and unstructured data.  ... 
doi:10.4018/jdcf.2011070101 fatcat:6uwgpaoonjfibpbejbs6kyy4cu

Prioritized Property-Value based Data Modelling for Big Data

Existing Big Data modelling includes mostly in handling structured data but no defined approach was designed for modelling Big Data which includes structured, semi-structured and unstructured data.  ...  The effectiveness of this innovative approach is sensed by modelling oncology data using MongoDB. This modelling facilitates ease analytics and is independent of context.  ...  This resulted in getting deposited with structured data, semi-structured data and unstructured data in major percentage.  ... 
doi:10.35940/ijitee.i1145.0789s219 fatcat:pkofvdmbkfc4nk3xkkojjvaekq

An Empirical Study of Effective and Versatile Keyword Query Search

Tejashree R. Shinde, Prof. Sanchika A. Bajpai
2015 International Journal of Engineering Research and  
In today's world, the huge amount of information is maintained and stored on World Wide Web.  ...  In this information searching is done with the help of keyword which is known as query keyword and searching is called as keyword searching.  ...  field and all my colleagues for providing help and support in my work.  ... 
doi:10.17577/ijertv4is050573 fatcat:ogylhz7p6rh7blto7nszeatjuu

Analyzing Analytics

Rajesh Bordawekar, Bob Blainey, Ruchir Puri
2015 Synthesis Lectures on Computer Architecture  
We are interested in isolating and documenting repeated patterns in analytical algorithms, data structures and data types, and in understanding how these could be most effectively mapped onto parallel  ...  Many organizations today are faced with the challenge of processing and distilling information from huge and growing collections of data.  ...  These data structures include vectors, matrices, graphs, trees, relational tables, lists, hash-based structures, and binary objects.  ... 
doi:10.2200/s00678ed1v01y201511cac035 fatcat:jkjywe5rzzaupjwq5rjyavqxi4

Extraction and Representation of Financial Entities from Text [chapter]

Tim Repke, Ralf Krestel
2021 Data Science for Economics and Finance  
Furthermore, data mining techniques can be used to enrich or filter knowledge graphs. This information can augment source documents and guide exploration processes.  ...  of this chapter considers applications based on knowledge graphs of automatically extracted facts.  ...  Extracting Knowledge Graphs from Text Many business insights are hidden in unstructured text. Modern NLP methods can be used to extract that information as structured data.  ... 
doi:10.1007/978-3-030-66891-4_11 fatcat:ssd2taqbezg3bp36w2lbo5te4u

Text Mining to Facilitate Domain Knowledge Discovery [chapter]

Chengbin Wang, Xiaogang Ma
2019 Text Mining - Analysis, Programming and Application [Working Title]  
Many findings and discoveries were recorded in the geological literature, which is regarded as unstructured data.  ...  Text mining based on natural language processing (NLP) provides the necessary method and technology to analyze unstructured geological literature.  ...  The majority of geological big data are unstructured, such as text and image. Previous mineral exploration mainly depends on derived information from the structured numeric data.  ... 
doi:10.5772/intechopen.85362 fatcat:opipq2cyhrfmjdnw2rewku7spy

Effective Use of Multiple Random Walks in P2P Networks

Zita Maria Almeida do Vale, Carlos Ramos, Rosslin John Robles
2014 Asia-pacific Journal of Multimedia services convergent with Art Humanities and Sociology  
Based on how the nodes are linked to each other within the overlay network, and how resources are indexed and located, we can classify networks as unstructured or structured (or as a hybrid between the  ...  Efficient and effective full-text retrieval over unstructured p2p networks was developed in order to address the problems of the query popularity independent replication strategies, previously a novel  ...  This paper explores, through simulation, various alternatives to Gnutella's query algorithm, data replication strategy, and network topology.  ... 
doi:10.14257/ajmscahs.2014.06.04 fatcat:lihfkrnavfcmnbdejiudumwaai

Interactive intervention analysis

David Gotz, Krist Wongsuphasawat
2012 AMIA Annual Symposium Proceedings  
A visualization-based user interface is provided to allow interactive exploration. We present an overview of the system and share clinician feedback regarding the prototype implementation.  ...  In this paper, we describe an interactive visualization-based system for intervention analysis and apply it to patients at risk of developing congestive heart failure (CHF).  ...  We then correlate this data with structured information about interventions (e.g., medications and procedures).  ... 
pmid:23304297 pmcid:PMC3540566 fatcat:njlneexsbndi5luatnew4v4phe

Semi-supervised learning for structured regression on partially observed attributed graphs [chapter]

Jelena Stojanovic, Milos Jovanovic, Djordje Gligorijevic, Zoran Obradovic
2015 Proceedings of the 2015 SIAM International Conference on Data Mining  
This method is aimed at learning with both labeled and unlabeled parts and effectively predicting future values in a graph.  ...  The benefits of the new method are also demonstrated on a challenging application for predicting precipitation based on partial observations of climate variables in a temporal graph that spans the entire  ...  (NN) and the available structure over the labeled data as described in Section 3.2.  ... 
doi:10.1137/1.9781611974010.25 dblp:conf/sdm/StojanovicJGO15 fatcat:gzvb4iexdrhitlmemrgz3ev3ri
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