Huge amounts of data have been stored in databases, data warehouses, geographic information systems, and other information repositories , and this data is still growing rapidly 4]. Companies are building data warehouses capable of storing hundreds of terabytes of data related to natural resource exploration; astronomical databases are measured in terabytes in size; and it is expected that the N...

The amount of generated and collected data has been rapidly increasing in the last decades; these huge data and information collections are far outpacing our abilities to analyse, summarize, and extract knowledge. This explosive growth in stored data has generated a need for new techniques that can help in transforming these large quantities of data into useful comprehensible knowledge. These t...

Knowledge management systems are making inroads into organizations that want to get a handle on their intellectual capital. To this end, we have designed and implemented Expert Seeker, an Expertise-Locator knowledge management system that will be used in several NASA Centers to identify experts within the organization. This paper presents the use of web data mining techniques to construct and m...

Data mining has proved its significance in various domains and applications. As an important subfield of the general data mining task, subgroup mining can be used, e.g., for marketing purposes in business domains, or for quality profiling and analysis in medical domains. The goal is to efficiently discover novel, potentially useful and ultimately interesting knowledge. However, in real-world si...

Data mining faces multiple defies, with improving its results through the use of domain knowledge at the top. The advent of domain driven data mining brings new techniques to use that knowledge. Educational data mining is a favored domain to explore such tools, both due to the advances in the area and the existence of domain knowledge. In this work, we propose a new methodology for anticipating...

Mining information and knowledge from large databases has been recognized by many researchers as a key research topic in database systems and machine learning, and by many industrial companies as an important area with an opportunity of major revenues. Researchers in many different fields have shown great interest in data mining. Several emerging applications in information providing services, ...

Text mining, as one major school in Knowledge Discovery in Data (KDD), mines hidden patterns, rules, regularities and trends from textual data / non-database-data (i.e., text files, web documents, etc.). It is quite different from data mining (another well-known major school in KDD): the data structure of texts, dealt by text mining, is considered implicit, whereas traditional database-data, de...

Text mining is a specific method to extract knowledge from structured and unstructured data. This extracted knowledge from text mining process can be used for further usage and discovery. This paper presents the method for extraction information from unstructured text data and the importance of Association Rules Mining, specifically for of Korean language (text) and also, NLP (Natural Language ...

In this study, data mining and knowledge discovery techniques were employed to validate their efficacy in acquiring information about the viscoelastic properties of vapor-grown carbon nanofiber (VGCNF)/ vinyl ester (VE) nanocomposites solely from data derived from a designed experimental study. Formulation and processing factors (VGCNF type, use of a dispersing agent, mixing method, and VGCNF w...

DaWaK 2003: 5th International Conference on Data Warehousing and Knowledge Discovery (September 35, 2003, Prague, Czech Repblic) Abstract--Data mining, or knowledge discovery in databases (KDD), is an interdisciplinary area that integrates techniques from several fields including machine learning, statistics, and database systems, for the analysis of large volumes of data. This paper reviews th...