This paper describes works on the application of Mining Unstructured Data (MUD) in software engineering. The paper briefly reviews the types of unstructured data available to researchers providing pointers to basic mining techniques to exploit them. Then, an overview o...
The applications of knowledge graph ranges from systems in healthcare16,17 to search systems and scientific document indexing8,16,17,18. In cybersecurity and cyber intelligence, the use of knowledge graphs and linked data has been prevalent due to the mostly structured nature of the recorded ...
In general, data mining is the practice of combing through data sets and trying to get just the most valuable bits of information into a specific format. This is typically more difficult with relatively unstructured data. IT experts define unstructured data as data that is not in a specific fo...
Ziv:I agree, but that is part of what is hindering growth. None of the applications that are out there today, and I have seen all of them, are 100 percent accurate. You may identify the word correctly, but if you don't understand the context of that word then you are missing the p...
How is unstructured data stored? Unstructured data can be stored in a number of ways: in applications, NoSQL (non-relational) databases, data lakes, and data warehouses. Platforms like MongoDB Atlas are especially well-suited for housing, managing, and using unstructured data. ...
Data Lakes Data lakes store unstructured data in its native or raw format. Unstructured data stored in data lakes includes output from systems, sensors, applications, and social media. Data lakes are often housed in cloud storage, such as Amazon Simple Storage Service (S3), Microsoft Azure Data...
Huge volumes of biomedical text data discussing about different biomedical entities are being generated every day. Hidden in those unstructured data are the strong relevance relationships between those entities, which are critical for many interesting applications including building knowledge bases for the ...
The main differences between structured and unstructured data include the type of analysis it can be used for, schema used, type of format and the ways it is stored. Traditional structured data, such as the transaction data in financial systems and other business applications, conforms to a rigi...
Section 2.2 overviews the literature of online review mining methods for healthcare management. Methodology This section proposes an FMCDM method to utilize unstructured data from online reviews of hospitals and structured evaluation data from publicly available attributes for hospital selection. The ...
Semantic presentation and fusion framework of unstructured data in smart cites. In Proceedings of the 10th IEEE Conference on Industrial Electronics and Applications (ICIEA 2015), Auckland, New Zealand, 5–17 June 2015; Volume 10, pp. 897–901. Goth, G. Digging deeper into text mining: ...