منابع مشابه
Knowledge Discovery from Data Streams
Traditional pratice in machine learning algorithms involve fixed data sets and static models. Most of the times, all the data is loaded into memory and the learning task is solved by performing multiple scans over the training data. These assumptions fail with the advent of new application areas, like ubiquitous computing, sensor networks, e-commerce, etc., where data flows continuously, eventu...
متن کاملResource-aware Knowledge Discovery in Data Streams
Mining data streams has raised a number of research challenges for the data mining community. These challenges include the limitations of computational resources, especially because mining streams of data most likely be done on a mobile device with limited resources. Also due to the continuality of data streams, the algorithm should have only one pass or less over the incoming data elements. In...
متن کاملKnowledge discovery from data?
(KDD) field draws on findings from statistics, databases, and artificial intelligence to construct tools that let users gain insight from massive data sets. People in business, science, medicine, academia, and government collect such data sets, and several commercial packages now offer general-purpose KDD tools. An important KDD goal is to “turn data into knowledge.” For example, knowledge acqu...
متن کاملKnowledge Discovery from Linked Data
Linked Data has been increasing rapidly by publishing machine readable structured data. DBpedia and YAGO are cross-domain data sets, which provide semantic knowledge of things. Although both data sets contain millions of entities, there are still missing knowledge exist in each data set. In this paper, we analyze graph patterns of Linked Data entities to discover missing knowledge in the data s...
متن کاملKnowledge discovery from sequential data
A new framework for analyzing sequential or temporal data such as time series is proposed. It differs from other approaches by the special emphasis on the interpretability of the results, since interpretability is of vital importance for knowledge discovery, that is, the development of new knowledge (in the head of a human) from a list of discovered patterns. While traditional approaches try to...
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ژورنال
عنوان ژورنال: Intelligent Data Analysis
سال: 2008
ISSN: 1571-4128,1088-467X
DOI: 10.3233/ida-2008-12301