Download Data Mining and Decision Support: Integration and by Dunja Mladenic, Nada Lavrač, Marko Bohanec, Steve Moyle PDF

By Dunja Mladenic, Nada Lavrač, Marko Bohanec, Steve Moyle

Data mining bargains with discovering styles in info which are via user-definition, fascinating and legitimate. it really is an interdisciplinary zone related to databases, desktop studying, trend reputation, records, visualization and others.
Decision help makes a speciality of constructing platforms to aid decision-makers remedy difficulties. determination aid presents a variety of knowledge research, simulation, visualization and modeling thoughts, and software program instruments resembling selection help structures, staff selection aid and mediation structures, professional structures, databases and knowledge warehouses.

Independently, facts mining and selection aid are well-developed examine components, yet previously there was no systematic try and combine them. Data Mining and selection aid: Integration and Collaboration, written through top researchers within the box, provides a conceptual framework, plus the equipment and instruments for integrating the 2 disciplines and for using this know-how to enterprise difficulties in a collaborative atmosphere.

Show description

Read Online or Download Data Mining and Decision Support: Integration and Collaboration PDF

Best data mining books

Computational Processing of the Portuguese Language: 11th International Conference, PROPOR 2014, São Carlos/SP, Brazil, October 6-8, 2014. Proceedings

This e-book constitutes the refereed complaints of the eleventh foreign Workshop on Computational Processing of the Portuguese Language, PROPOR 2014, held in Sao Carlos, Brazil, in October 2014. The 14 complete papers and 19 brief papers awarded during this quantity have been conscientiously reviewed and chosen from sixty three submissions.

Exploring the Design and Effects of Internal Knowledge Markets

This booklet investigates the layout and implementation of marketplace mechanisms to discover how they could aid wisdom- and innovation administration inside of businesses. The e-book makes use of a multi-method layout, combining qualitative and quantitative instances with experimentation. First the booklet experiences conventional methods to fixing the matter in addition to markets as a key mechanism for challenge fixing.

Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving

This booklet provides case stories in statistical computing for info research. each one case learn addresses a statistical software with a spotlight on evaluating diverse computational techniques and explaining the reasoning at the back of them. The case stories can function fabric for teachers instructing classes in statistical computing and utilized facts.

Data Mining and Machine Learning in Building Energy Analysis: Towards High Performance Computing

Concentrating on up to date synthetic intelligence versions to resolve development power difficulties, synthetic Intelligence for construction strength research reports lately built versions for fixing those concerns, together with distinctive and simplified engineering tools, statistical tools, and synthetic intelligence equipment.

Additional resources for Data Mining and Decision Support: Integration and Collaboration

Sample text

Van (1979), Information Retrieval, Butterworths. , Karypis, G. and Kumar, V. (2000). A comparison of document clustering techniques. Proc. KDD Workshop on Text Mining. (eds. , Mladenic, D. ), Boston, MA, USA, 109-110. Chapter 3 DECISION SUPPORT Marko Bohanec Abstract: 1. This chapter describes and clarifies the meaning of the term decision support. Taking a broad view, a classification of decision support and related disciplines is presented. Decision support is put in the context of decision making, and an overview of some of the most important disciplines within decision support is provided including: operations research, decision analysis, decision support systems, data warehousing, and group decision support.

What are the most important differences between them? Are the evaluations in accordance with expectations? If not, why? Does the model seem correct? What about the utility functions and option descriptions? Can we explain the obtained evaluations? Which are the most important strong and weak points of the various options? How sensitive is the options ranking to small changes in the utility functions? Decision support 33 Phase 6: Choice The actual choice is based on evidence collected in previous phases.

In the content-based approach to information filtering, the system searches for the items similar to those the user liked based on the content comparison. For instance, observing the user browsing the Web and providing help by highlighting potentially interesting hyperlinks on the requested Web pages (Mladenic, 2002). Content-based document filtering has its foundation in information retrieval research. , music, movies, and images). In addition to the representation problems, content-based systems tend to specialize the search for items similar to the ones already seen by the user.

Download PDF sample

Rated 4.29 of 5 – based on 24 votes