Slovenian KDD Conference on Data Mining and Data Warehouses (SiKDD), Ljubljana 2008

Slovenian KDD Conference on Data Mining and Data Warehouses (SiKDD), Ljubljana 2008

10 Lectures · Oct 17, 2008

About

Data handling technologies have significantly progressed in the last ten years. The first phases mainly dealing with storing and efficiently accessing the data, resulted in the development of industry delivering tools for handling large databases, standardization of related processes, queering languages, etc. When the data storage was not a primary problem any more the need for improving the database organization resulted in the databases supporting not only transactions but also analytical views of the data.

At this point data warehousing with OLAP (On-Line-Analytical-Processing) entered as a usual part of a company information system. The OLAP paradigme stil requires from the user to set well defined questions which is not always easy and possible. This led to the development of Data Mining offering automatic data analysis trying to obtain some new information from the existing data and enabling the user some new insights in the data. Further development of methods for Text Mining enables handling textual data in addition to well structured data in databases. Large amount of data and activities on the Web is further addressed in Web Mining where in addition to content of the Web documents, the structure of the Web and Web log-files are analysed.

Link to the Conference Page - http://kt.ijs.si/Dunja/SiKDD2008/

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Algorithms: Text Mining and Natural Language Processing

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Triplet Extraction from Sentences

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Semantic Graphs Derived from Triplets with Application in Document Summarization

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Stochastic Subgradient Approach for Solving Linear Support Vector Machines

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Algorithms: Data Mining and Machine Learning

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A Functional Programming Approach to Distance-based Machine Learning

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Applications of Semantic Technologies and Machine Learning

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Extending Ontologies for Annotating Business News

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Semantic Modeling, Translation and Matching of QoS

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Hierarchical Annotation of Medical Images

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Applications of Data Mining and Machine Learning

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The Statistical Interpretation of Simulated Emergency Breaking Event Time Series...

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Churn Prediction Model in Retail Banking Using Fuzzy C-Means Clustering

Džulijana Popović

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