Improving the SLA Algorithm Using Association Rules

نویسندگان

  • Evelina Lamma
  • Fabrizio Riguzzi
  • Andrea Stambazzi
  • Sergio Storari
چکیده

A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for bayesian network learning. Some of them are based on search and score methodology and the others follow an information theory based approach. One of the most known algorithm for learning bayesian network is the SLA algorithm. This algorithm constructs a bayesian network by analyzing conditional independence relationships among nodes. The SLA algorithm has three phases: drafting, thickening and thinning. In this work, we propose an alternative method for performing the drafting phase. This new methodology uses data mining techniques, and in particular the computation of a number of parameters usually defined in relation to association rules, in order to learn an initial structure of a bayesian network. In this paper, we present the BNL-rules algorithm (Bayesian Network Learner with association rules) that exploits a number of association rules parameters to infer the structure of a bayesian network. We will also present the comparisons between SLA and BNL-rules algorithms on learning four bayesian networks.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Using a Data Mining Tool and FP-Growth Algorithm Application for Extraction of the Rules in two Different Dataset (TECHNICAL NOTE)

In this paper, we want to improve association rules in order to be used in recommenders. Recommender systems present a method to create the personalized offers. One of the most important types of recommender systems is the collaborative filtering that deals with data mining in user information and offering them the appropriate item. Among the data mining methods, finding frequent item sets and ...

متن کامل

Identifying and Evaluating Effective Factors in Green Supplier Selection using Association Rules Analysis

Nowadays companies measure suppliers on the basis of a variety of factors and criteria that affect the supplier's selection issue. This paper intended to identify the key effective criteria for selection of green suppliers through an efficient algorithm callediterative process mining or i-PM. Green data were collected first by reviewing the previous studies to identify various environmental cri...

متن کامل

Applying a decision support system for accident analysis by using data mining approach: A case study on one of the Iranian manufactures

Uncertain and stochastic states have been always taken into consideration in the fields of risk management and accident, like other fields of industrial engineering, and have made decision making difficult and complicated for managers in corrective action selection and control measure approach. In this research, huge data sets of the accidents of a manufacturing and industrial unit have been st...

متن کامل

Introducing an algorithm for use to hide sensitive association rules through perturb technique

Due to the rapid growth of data mining technology, obtaining private data on users through this technology becomes easier. Association Rules Mining is one of the data mining techniques to extract useful patterns in the form of association rules. One of the main problems in applying this technique on databases is the disclosure of sensitive data by endangering security and privacy. Hiding the as...

متن کامل

Mining the Banking Customer Behavior Using Clustering and Association Rules Methods

  The unprecedented growth of competition in the banking technology has raised the importance of retaining current customers and acquires new customers so that is important analyzing Customer behavior, which is base on bank databases. Analyzing bank databases for analyzing customer behavior is difficult since bank databases are multi-dimensional, comprised of monthly account records and daily t...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2003