Modifying Logic of Discovery for Dealing with Domain Knowledge in Data Mining
نویسنده
چکیده
Logic of discovery was developed in 1970’s as an answer to questions ”Can computers formulate and justify scientific hypotheses?” and ”Can they comprehend empirical data and process it rationally, using the apparatus of modern mathematical logic and statistics to try to produce a rational image of the observed empirical world?”. Logic of discovery is based on observational and theoretical languages and on inductive inference corresponding to statistical approaches. Formulas of observational language concern analyzed observational data and formulas of theoretical language concern suitable state dependent structures. The goal of the paper is to discuss a possibility to adapt the logic of discovery to data mining.
منابع مشابه
Expert Discovery: A web mining approach
Expert discovery is a quest in search of finding an answer to a question: “Who is the best expert of a specific subject in a particular domain within peculiar array of parameters?” Expert with domain knowledge in any field is crucial for consulting in industry, academia and scientific community. Aim of this study is to address the issues for expert-finding task in real-world community. Collabor...
متن کاملA Logical Framework for Frequent Pattern Discovery in Spatial Data
In recent times, several extensions f data mining methods and techniques have been explored aiming at dealing with advanced databases. Many promising applications of inductive logic programming (ILP) to knowledge discovery in databases have also emerged inorder to benefit from semantics andinference rules of first-order logic. Inthis paper, an ILP framework forfrequent pattern discovery in spat...
متن کاملخوشهبندی اسناد مبتنی بر آنتولوژی و رویکرد فازی
Data mining, also known as knowledge discovery in database, is the process to discover unknown knowledge from a large amount of data. Text mining is to apply data mining techniques to extract knowledge from unstructured text. Text clustering is one of important techniques of text mining, which is the unsupervised classification of similar documents into different groups. The most important step...
متن کاملارائه مدلی برای استخراج اطلاعات از مستندات متنی، مبتنی بر متنکاوی در حوزه یادگیری الکترونیکی
As computer networks become the backbones of science and economy, enormous quantities documents become available. So, for extracting useful information from textual data, text mining techniques have been used. Text Mining has become an important research area that discoveries unknown information, facts or new hypotheses by automatically extracting information from different written documents. T...
متن کاملApplication of Rough Set Theory in Data Mining for Decision Support Systems (DSSs)
Decision support systems (DSSs) are prevalent information systems for decision making in many competitive business environments. In a DSS, decision making process is intimately related to some factors which determine the quality of information systems and their related products. Traditional approaches to data analysis usually cannot be implemented in sophisticated Companies, where managers ne...
متن کامل